Process detection is a fundamental problem arising in a variety of homeland security, national defense and commercial applications, including network security, sensor network data fusion, dynamic social network analysis and video tracking of kinematic objects. Our approach to process detection is based on a generic algorithmic approach called Process Query Systems which has been developed at Dartmouth over the past 3 years. This paper surveys the general area of process detection, its applications and recent progress made in various implementations.

Within an organization, the possibility of a confidential information leak ranks among the highest fears of any executive. Detecting information leaks is a challenging problem, since most organizations depend on a broad and diverse communications network. It is not always straightforward to conclude which information is leaving the organization legitimately, and which communications are malicious data exfiltrations. Sometimes it is not even possible to tell that a communication is occurring at all. The set of all possible exfiltration methods contains, at a minimum, the set of all possible information communication methods, and possibly more. This article cannot possibly cover all such methods; however, several notable examples are given, and a taxonomy of data exfiltration is developed. Such a taxonomy cannot ever be exhaustive, but at the very least can offer a framework for organizing methods and developing defenses.

The pervasiveness of software and networked information systems is evident across a broad spectrum of business and government sectors. Such reliance provides an ample opportunity not only for the nefarious exploits of lone wolf computer hackers, but for more systematic software attacks from organized entities. Much effort and focus has been placed on preventing and ameliorating network and OS attacks, a concomitant emphasis is required to address protection of mission critical software. Typical software protection technique and methodology evaluation and verification and validation (V&V) involves the use of a team of subject matter experts (SMEs) to mimic potential attackers or hackers. This manpower intensive, time-consuming, and potentially cost-prohibitive approach is not amenable to performing the necessary multiple non-subjective analyses required to support quantifying software protection levels. To facilitate the evaluation and V&V of software protection solutions, we have designed and developed a prototype adaptive cyber attack modeling system. Our approach integrates an off-line mechanism for rapid construction of Bayesian belief network (BN) attack models with an on-line model instantiation, adaptation and knowledge acquisition scheme. Off-line model construction is supported via a knowledge elicitation approach for identifying key domain requirements and a process for translating these requirements into a library of BN-based cyber-attack models. On-line attack modeling and knowledge acquisition is supported via BN evidence propagation and model parameter learning.

The detection and tracking of embedded malicious subnets in an active social network can be computationally daunting due to the quantity of transactional data generated in the natural interaction of large numbers of actors comprising a network. In addition, detection of illicit behavior may be further complicated by evasive strategies designed to camouflage the activities of the covert subnet. In this work, we move beyond traditional static methods of social network analysis to develop a set of dynamic process models which encode various modes of behavior in active social networks. These models will serve as the basis for a new application of the Process Query System (PQS) to the identification and tracking of covert dynamic processes in social networks. We present a preliminary result from application of our technique in a real-world data stream— the Enron email corpus.

One significant drawback to currently available security products is their inabilty to correlate diverse sensor input. For instance, by only using network intrusion detection data, a root kit installed through a weak username-password combination may go unnoticed. Similarly, an administrator may never make the link between deteriorating response times from the database server and an attacker exfiltrating trusted data, if these facts aren't presented together. Current Security Information Management Systems (SIMS) can collect and represent diverse data but lack sufficient correlation algorithms. By using a Process Query System, we were able to quickly bring together data flowing from many sources, including NIDS, HIDS, server logs, CPU load and memory usage, etc. We constructed PQS models that describe dynamic behavior of complicated attacks and failures, allowing us to detect and differentiate simultaneous sophisticated attacks on a target network. In this paper, we discuss the benefits of implementing such a multistage cyber attack detection system using PQS. We focus on how data from multiple sources can be combined and used to detect and track comprehensive network security events that go unnoticed using conventional tools.

We have developed a general framework, called a Process Query System (PQS), that serves as a foundation for formulating tracking problems, implementing software solutions to tracking problems and understanding theoretical issues related to tracking in specific scenarios. The PQS framework posits that an environment consists of multiple dynamical processes. Processes have states, state transitions (deterministic, nondeterministic or probabilistic) and observables related to state occupancy. Examples of such dynamical processes are nondeterministic automata, Hidden Markov Models and classical state space models. We define a tracking problem as the inverse problem of determining the processes and process states that explain a stream of observations. This paper describes a quantitative concept of trackability by considering the rate of growth of state sequences of a process model given a temporal sequence of observations. Recent formal results concerning this notion of trackability are summarized without proof. Complete proofs of the various results are contained in a technical report by the authors and cited in the bibliography.

Bio-computing model of 'Distributed Multiple Intelligent Agents Systems' (BDMIAS) models agents as genes, a cooperating group of agents as operons - commonly regulated groups of genes, and the complex task as a set of interacting pathways such that the pathways involve multiple cooperating operons. The agents (or groups of agents) interact with each other using message passing and pattern based bindings that may reconfigure agent's function temporarily. In this paper, a technique has been described for incorporating fault tolerance in BDMIAS. The scheme is based upon simulating BDMIAS, exploiting the modeling of biological stress pathways, integration of fault avoidance, and distributed fault recovery of the crashed agents. Stress pathways are latent pathways in biological system that gets triggered very quickly, regulate the complex biological system by temporarily regulating or inactivating the undesirable pathways, and are essential to avoid catastrophic failures. Pattern based interaction between messages and agents allow multiple agents to react concurrently in response to single condition change represented by a message broadcast. The fault avoidance exploits the integration of the intelligent processing rate control using message based loop feedback and temporary reconfiguration that alters the data flow between functional modules within an agent, and may alter. The fault recovery exploits the concept of semi passive shadow agents - one on the local machine and other on the remote machine, dynamic polling of machines, logically time stamped messages to avoid message losses, and distributed archiving of volatile part of agent state on distributed machines. Various algorithms have been described.

The communication of Future Combat Systems (FCS), with rigid timing and reliability requirements, has posed a great challenge for the existing popular transport layer protocols such as TCP and UDP. The Stream Control Transmission Protocol (SCTP), first designed to transmit telephony signaling messages over Internet, is a promising transport layer candidate for FCS networks. The new SCTP features such as multi-homing, multi-streaming, and enhanced security can significantly improve the performance of FCS applications. In this paper, we propose modifications to the congestion control and multi-streaming parts of current SCTP specifications to allow the support of QoS for FCS applications. Multiple streams in an SCTP association provide an aggregation mechanism to accommodate heterogeneous objects, which belong to the same application but may require different types of QoS from the network. However, the current SCTP specification lacks an internal mechanism to support the preferential treatment among its streams. Our work introduces the concept of grouping SCTP streams into subflows based on their required QoS. We propose to modify the current SCTP to implement subflows (named SF-SCTP), each with its own flow and congestion mechanism to prevent the so-called false sharing problem. To improve the fairness of SF-SCTP towards the original SCTP, we integrate Fractional Congestion Control into the design. The throughput performance evaluation of SF-SCTP is studied through ns-2 experiments in a simplified Diff-Serv network. The simulation results prove the SF-SCTP's capability to support QoS among its streams, confirm the accuracy of the analytic models, and justify our effects to integrate FCC into SF-SCTP since it improves the fairness between SF-SCTP and the original SCTP.

In this paper, we propose a new approach to routing protocol called information-aware collaborative routing for wireless sensor networks. Clustering and local data aggregation schemes have been developed to reduce the energy for transmitting redundant data in the wireless sensor network. Most existing approaches have been developed for the cases when there is direct communication between cluster head and base station. Even though these schemes are able to reduce data redundancy to be transmitted from the cluster heads to the base station, they have not exploited the data redundancy between neighboring clusters. In this research, we study a more general case when there are multi-hop communications from cluster heads to the base station. To exploit the potential redundancy between neighboring clusters, we propose to develop a routing protocol architecture that combines multi-hop routing with information-aware clustering based on the correlation of sensor data. The information-aware collaborative routing includes the re-clustering based on data correlation as well as the central-controlled clustering and cluster heads rotation to evenly distribute the energy load in the entire network. Extensive simulations show that the proposed information-aware collaborative routing can achieve better performance in terms of longer network lifetime and less energy dissipation comparing with the existing cluster-based routing.

One of the most important design issues in wireless sensor networks is energy efficiency. Data aggregation has significant impact on the energy efficiency of the wireless sensor networks. With massive deployment of sensor nodes and limited energy supply, data aggregation has been considered as an essential paradigm for data collection in sensor networks. Recently, distributed source coding has been demonstrated to possess several advantages in data aggregation for wireless sensor networks. Distributed source coding is able to encode sensor data with lower bit rate without direct communication among sensor nodes. To ensure reliable and high throughput transmission with the aggregated data, we proposed in this research a progressive transmission and decoding of Rate-Compatible Punctured Convolutional (RCPC) coded data aggregation with distributed source coding. Our proposed 1/2 RSC codes with Viterbi algorithm for distributed source coding are able to guarantee that, even without any correlation between the data, the decoder can always decode the data correctly without wasting energy. The proposed approach achieves two aspects in adaptive data aggregation for wireless sensor networks. First, the RCPC coding facilitates adaptive compression corresponding to the correlation of the sensor data. When the data correlation is high, higher compression ration can be achieved. Otherwise, lower compression ratio will be achieved. Second, the data aggregation is adaptively accumulated. There is no waste of energy in the transmission; even there is no correlation among the data, the energy consumed is at the same level as raw data collection. Experimental results have shown that the proposed distributed data aggregation based on RCPC is able to achieve high throughput and low energy consumption data collection for wireless sensor networks

The Dual Energy X-ray technique employs two X-ray projection images of an object with X-ray energy spectra at a low X-ray energy and a high X-ray energy. The two energies are both high enough to penetrate all cargoes. The endpoint energies for low and high will be approximately 5-6 MeV and 8-9.5 MeV respectively. These energies are chosen such that pair production is the dominant energy loss mechanism for the high energy mode. By defining the ratio of the transmitted X-ray photon R = T_high/T_low it can be shown that there is a difference in the ratio that will permit the detection of materials that are significantly higher in atomic number than the low to mid atomic numbered elements that normally appear in the stream of commerce. This difference can be used to assist in the automatic detection of high atomic numbered materials. These materials might be a WMD or dirty bomb. When coupled with detectors that can observe the delayed signature of photon induced fission a confirmation of a WMD may be made. The use of the delayed photons and neutrons from Photofission can confirm the presence of Special Nuclear Materials (SNM). The energy required to induce fission in SNM by a photon is approximately 6 MeV with the maximum fission production rate from X-ray photons in the energy range of 12-15 MeV.

Government agencies and homeland security related organizations have identified the need to develop and establish a wide range of unprecedented capabilities for providing scientific and technical forensic services to investigations involving hazardous chemical, biological, and radiological materials, including extremely dangerous chemical and biological warfare agents. Pacific Northwest National Laboratory (PNNL) has developed a prototype portable, handheld, hazardous materials acoustic inspection prototype that provides noninvasive container interrogation and material identification capabilities using nondestructive ultrasonic velocity and attenuation measurements. Due to the wide variety of fluids as well as container sizes and materials encountered in various law enforcement inspection activities, the need for high measurement sensitivity and advanced ultrasonic measurement techniques were identified. The prototype was developed using a versatile electronics platform, advanced ultrasonic wave propagation methods, and advanced signal processing techniques. This paper primarily focuses on the ultrasonic measurement methods and signal processing techniques incorporated into the prototype. High bandwidth ultrasonic transducers combined with an advanced pulse compression technique allowed researchers to 1) obtain high signal-to-noise ratios and 2) obtain accurate and consistent time-of-flight (TOF) measurements through a variety of highly attenuative containers and fluid media. Results of work conducted in the laboratory have demonstrated that the prototype experimental measurement technique also provided information regarding container properties, which will be utilized in future container-independent measurements of hidden liquids.

The ultimate problem for trace detection is sampling. More sensors are needed in more places to successfully tackle the sampling problem-especially for low vapor pressure explosives that are difficult to detect from a distance. To solve this problem, compact, inexpensive, and robust systems are needed that have not sacrificed sensitivity or selectivity to achieve their goals. In response, Nevada Nanotech Systems, Inc (NNTS) is developing microcantilever-based Self-Sensing Array™ (SSA) technology that will measure trace concentrations of explosives, toxic chemicals, and biological agent signatures in air. Ultimately, this technology could enable a device that would measure about two cubic inches, run on a small watch battery and cost a few hundred dollars. This paper compares the selectivity of SSA technology to other detection technologies using the metric of orthogonal channel capacity (OCC).

A simple through-the-wall radar system for moving target localization is proposed. This scheme is based on trilateration and range estimation from three independent dual-frequency CW radar units. The dual-frequency technique uses phase comparison of the transmitted and received CW signals to provide an estimate of the range-to-motion. The difference in frequency of the two CW carriers determines the maximum unambiguous range of the target. The range estimates from the three independent CW radar units are then combined using trilateration for target localization. The composition and thickness of the wall, its dielectric constant, and the angle of incidence all affect the characteristics of the signal propagating through the wall. The propagating signal slows down, encounters refraction, and is attenuated as it passes through the wall. If unaccounted for, the non-line-of-sight propagation due to refraction and the slowing down of the waves will introduce a bias in the estimated target location. Our scheme takes into account the presence of the wall and corrects for its refraction and speed of propagation effects. Proof of concept is provided using simulated data. The results show that the proposed dual-frequency CW radar system is able to correctly locate and track moving targets behind walls.

We describe the architecture and design of a through-the-wall radar. The radar is applied for the detection and localization of people hidden behind obstacles. It implements a new adaptive processing technique for people detection, which is introduced in this article. This processing technique is based on exponential averaging with adopted weighting coefficients. Through-the-wall detection and localization of a moving person is demonstrated by a measurement example. The localization relies on the time-of-flight approach.

A new technical approach for 'Through Wall Imaging', implemented with in the Xaver 800 system is introduced in this paper. The system is a portable Ultra-wideband (UWB) micro power radar that offers a comprehensive solution for field operational use. The Xaver 800 gives the user fast and reliable 3D visual information, the system shows objects situated behind walls with sufficient resolution such that a person can be observed including his different body parts. Enabling rich imaging capabilities and ease of use, the Xaver 800 gives the user the ability to make the right decisions and to run more efficient 'life saving' operations. One of the main problems with the current available through wall technologies is their low resolution, "Blob" like results limits their ability to be an effective tool in the field. Higher resolution can theoretically be achieved by widening the bandwidth of the UWB signals used in these systems. However, working with high bandwidth signals creates other challenges such as the un-alignment problem. Multi channels unaligned system can result in unfocused and distorted images. This paper deals with the un-alignment problem and suggests a few methods to solve it by coherent registration. Experimental results are given to prove the effectiveness of the different methods proposed.

In this keynote address, we introduce three-dimensional (3D) passive sensing using photon counting integral imaging. We investigate both linear and nonlinear matched filtering for automatic target recognition (ATR). Significant benefits of the nonlinear matched filtering with 3D integral imaging are found for ATR with a low number of photons. The discrimination capability of our system is quantified in terms of discrimination ratio (DR), Fisher ratio (FR), and receiver operating characteristic (ROC) curves. Experimental and simulation results are presented.

Advanced Optical Systems, Inc. developed the ULTOR(r) system, a real-time correlation processor that looks for improvised explosive devices (IED) by examining imagery of vehicles. The system determines the level of threat an approaching vehicle may represent. The system works on incoming video collected at different wavelengths, including visible, infrared, and synthetic aperture radar. Sensors that attach to ULTOR can be located wherever necessary to improve the safety around a checkpoint. When a suspect vehicle is detected, ULTOR can track the vehicle, alert personnel, check for previous instances of the vehicle, and update other networked systems with the threat information. The ULTOR processing engine focuses on the spatial frequency information available in the image. It correlates the imagery with templates that specify the criteria defining a suspect vehicle. It can perform full field correlations at a rate of 180 Hz or better. Additionally, the spatial frequency information is applied to a trained neural network to identify suspect vehicles. We have performed various laboratory and field experiments to verify the performance of the ULTOR system in a counter IED environment. The experiments cover tracking specific targets in video clips to demonstrating real-time ULTOR system performance. The selected targets in the experiments include various automobiles in both visible and infrared video.

In this paper, we present a framework for tracking multiple mobile targets in an urban environment based on data from multiple sources of information, and for evaluating the threat these targets pose to assets of interest (AOI). The motivating scenario is one where we have to track many targets, each with different (unknown) destinations and/or intents. The tracking algorithm is aided by information about the urban environment (e.g., road maps, buildings, hideouts), and strategic and intelligence data. The tracking algorithm needs to be dynamic in that it has to handle a time-varying number of targets and the ever-changing urban environment depending on the locations of the moving objects and AOI. Our solution uses the variable structure interacting multiple model (VS-IMM) estimator, which has been shown to be effective in tracking targets based on road map information. Intelligence information is represented as target class information and incorporated through a combined likelihood calculation within the VS-IMM estimator. In addition, we develop a model to calculate the probability that a particular target can attack a given AOI. This model for the calculation of the probability of attack is based on the target kinematic and class information. Simulation results are presented to demonstrate the operation of the proposed framework on a representative scenario.

Modern computational capabilities allow the practical application of Multiple Hypothesis Tracking (MHT) for difficult tracking conditions. However, even in typical expected scenarios, periods of unusually high target and / or clutter density may occur that stress the ability of MHT to operate in real-time and under the constraints of limited computer memory. This paper outlines methods that are being developed to ensure practical application, even though some performance degradation must be accepted, during these difficult conditions. These methods include the adaptive choice of track and hypothesis pruning parameters, IMM filtering models and new track initiation strategies as a function of the latency between the time that current observations are received and the track processing time. Methods to ensure that memory constraints are satisfied are also discussed. The methods are illustrated with examples from simulated missile defense scenarios where periods of very high target density are expected and a ground target tracking scenario with real radar data.

The proliferation of weapons of mass destruction (WMD) and the use of such elements pose an eminent asymmetric threat with disastrous consequences to the national security of any nation. In particular, the use of biochemical warfare agents against civilians and unprotected troops in international conflicts or by terrorists against civilians is considered as a very peculiar threat. Accordingly, taking a quarantine-before-inhalation approach to biochemical warfare, the author introduces the notion of autonomous biochemical decontamination against WMD. In the unfortunate event of a biochemical attack, the apparatus proposed herein is intended to automatically detect, identify, and more importantly neutralize a biochemical threat. Along with warnings concerning a cyber-WMD nexus, various sections cover discussions on human senses and computer sensors, corroborating evidence related to detection and neutralization of chemical toxins, and cyber-assisted olfaction in stand alone, peer-to-peer, and network settings. In essence, the apparatus can be used in aviation and mass transit security to initiate mass decontamination by dispersing a decontaminant aerosol or to protect the public water supply against a potential bioterrorist attack. Future effort may involve a system-on-chip (SoC) embodiment of this apparatus that allows a safer environment for the emerging phenomenon of cyber-assisted olfaction and morph cell phones into ubiquitous sensors/decontaminators. Although this paper covers mechanisms and protocols to avail a neutralizing substance, further research will need to explore the substance's various pharmacological profiles and potential side effects.

Novel mass-sensitive, magnetostrictive sensors have a characteristic resonant frequency that can be determined by monitoring the magnetic flux emitted by the sensor in response to an applied, time varying, magnetic field. This magnetostrictive platform has a unique advantage over conventional sensor platforms in that measurement is wireless or remote. These biosensors can thus be used in-situ for detecting pathogens and biological threat agents. In this work, we have used a magnetostrictive platform immobilized with a polyclonal antibody (the bio-molecular recognition element) to form a biosensor for the detection of Salmonella typhimurium. Upon exposure to solutions containing Salmonella typhimurium bacteria, the bacteria were bound to the sensor and the additional mass of the bound bacteria caused a shift in the sensor's resonant frequency. Responses of the sensors to different concentrations of S. typhimurium were recorded and the results correlated with those obtained from scanning electron microscopy (SEM) images of samples. Good agreement between the measured number of bound bacterial cells (attached mass) and frequency shifts were obtained. The longevity and specificity of the selected polyclonal antibody were also investigated and are reported.

Early detection and estimation of the spread of a biochemical contaminant are major issues for homeland security applications. We present an integrated approach combining the measurements given by an array of biochemical sensors with a physical model of the dispersion and statistical analysis to solve these problems and provide system performance measures. We approximate the dispersion model of the contaminant in a realistic environment through numerical simulations of reflected stochastic diffusions describing the microscopic transport phenomena due to wind and chemical diffusion using the Feynman-Kac formula. We consider arbitrary complex geometries and account for wind turbulence. Localizing the dispersive sources is useful for decontamination purposes and estimation of the cloud evolution. To solve the associated inverse problem, we propose a Bayesian framework based on a random field that is particularly powerful for localizing multiple sources with small amounts of measurements. We also develop a sequential detector using the numerical transport model we propose. Sequential detection allows on-line analysis and detecting wether a change has occurred. We first focus on the formulation of a suitable sequential detector that overcomes the presence of unknown parameters (e.g. release time, intensity and location). We compute a bound on the expected delay before false detection in order to decide the threshold of the test. For a fixed false-alarm rate, we obtain the detection probability of a substance release as a function of its location and initial concentration. Numerical examples are presented for two real-world scenarios: an urban area and an indoor ventilation duct.

A low-cost infrared sensor that uses room temperature pyroelectric detectors integrated with bandpass filters to provide low-resolution spectral scans of the absorption characteristics of hazardous chemicals was developed for fixed security applications. The sensor provides fast (1 s) and continuous monitoring, detection, and identification capabilities. A unique detection and identification algorithm that uses non-linear computation techniques to account for the exponential nature of optical absorption was developed. Chemical detection and identification is achieved by matching the recorded sensor response vector to an updatable signature library that currently includes the signatures of 14 chemicals. The sensor and algorithm were tested by introducing methanol vapor at optical depths between 225 - 270 ppm-m. Using 1 s signal samples obtained during approximately 20 min. test, resulted in no false positive alarms and 3.4% of false negatives. All false negatives were shown to be due to misidentification of methanol as isopropanol, which is spectrally similar to methanol. By grouping isopropanol with methanol the rate of false negatives was reduced to 0%. Results of the same test using a 30 s signal integration time resulted in no false positive and no false negative alarms.

An optical sensor has been designed and developed to measure transmitted light through water samples for the retrieval of total suspended solids TSS concentrations. The proposed optical system uses light emitting diodes LEDs to transmit light through the total suspended solids in water samples. The transmitted radiation values were obtained from output voltage readings of the multimeter of the optical detector. The voltage readings are correlated with the TSS concentrations of the samples. A developed algorithm was used to determine the relationship between these two parameters. The results showed a good correlation between the radiation values and the total suspended solids TSS concentrations. The accuracy is high and low value of the root mean square.

Modern information systems that are designed to plan for and respond to Chemical, Biological, and Radiological (CBR) attacks are now attempting to include airborne contaminant plume models in their application package. These plume models are a necessary component for the emergency personnel responding to an actual event and to those charged with developing an effective response plan in advance. The capabilities to create a variety of CBR-event scenarios quickly, to determine possible contaminant agent release locations from reports and sensor data, and to predict the path of a plume before it gets there, are functions that many involved in the military and homeland security will find beneficial. For this reason CT-Analyst's ability to generate accurate, time-dependant plumes that can be rendered much faster than real-time and can be adjusted and modified on the screen, is an incredible asset to developers of these civil defense systems. The value of the fast, accurate CT-Analyst computer models for complex urban terrain is greatly increased when the capabilities can be imported into platforms users and developers are already taking advantage of. CT-Analyst's strengths can now be accessed through other applications, GIS tools, and development environments. This process will be described to show how this is possible, to which systems it can be applied, and what benefits can result.

A novel optical sensor equipment has been developed for the measurement of total suspended solids TSS concentrations. The sensing equipment makes use of light-emitting diodes, LED's, as sources, and a silicon photodiode as a detector. The photodetector detects light scattered at 90°. The signal was correlated with the measured TSS concentrations. Scattered light was measured in terms of the output voltage of the photodetector of the proposed optical system. The output voltage was read using a conventional voltmeter. The correlation coefficient produced was high and the root mean square error was low.

In most field robots, go or no-go decision depends on the maximum height of a bump. For combat vehicles, however, much advanced capability of the vehicle is required to pass over a higher bump compared to its wheel radius. For this purpose, many combat vehicles are using variable geometry suspension (VGS). In this paper, a 6x6 vehicle with a rotating VGS was designed. Computer simulations of the designed vehicle were carried out with the ADAMS program to estimate motor capacity and the required torque. The suspension was designed to rotate 360 degrees about the swing axis, thus, the vehicle could climb a higher bump by rotating its suspension.

First Responders need tools that allow for visual assessment of developing situations, identification and location of potential threats, identification and location of victims, and to establish ingress/egress plans. This paper reports the development of a highly portable aerial surveillance robot which has indefinite flight aloft time, capability for both close-quarter and high-level surveillance operations, secure copper communications, and a variety of sensor configurations which can be easily reconfigured to meet mission needs.

In this paper, we propose a novel acoustic sensor network system that can provide road edge detection in order to prevent rollovers. The system can work in "non-cooperative" road scenarios that do not possess any characteristic "cooperative markings," such as white lines, or pavement at the sidewalk.

This paper presents several receiver structures for Chirp Slope Keying (CSK), a digital broadband modulation scheme we propose to use for underwater acoustical communications. In its simplest form, the binary information modulates the slope of a linear chirp, with up-chirps representing ones and down-chirps representing zeros. A time-domain receiver and a novel time-frequency receiver structure based on the Wigner distribution and the Radon Transform are discussed and evaluated in terms of the probability of error versus Signal-to-Noise (SNR) performance. Simulation results and plots are presented for the Additive White Gaussian Noise (AWGN) channel. Results show that if the detector at the receiver operates directly on the slope of the received signal, performance is improved at the expense of computational complexity.

Tunnels have been used to evade security of defensive positions both during times of war and peace for hundreds of years. Tunnels are presently being built under the Mexican Border by drug smugglers and possibly terrorists. Several have been discovered at the border crossing at Nogales near Tucson, Arizona, along with others at other border towns. During this war on terror, tunnels under the Mexican Border pose a significant threat for the security of the United States. It is also possible that terrorists will attempt to tunnel under strategic buildings and possibly discharge explosives. The Center for Cave and Karst Study (CCKS) at Western Kentucky University has a long and successful history of determining the location of caves and subsurface voids using microgravity technology. Currently, the CCKS is developing a remotely controlled robot which will be used to locate voids underground. The robot will be a remotely controlled vehicle that will use microgravity and GPS to accurately detect and measure voids below the surface. It is hoped that this robot will also be used in military applications to locate other types of voids underground such as tunnels and bunkers. It is anticipated that the robot will be able to function up to a mile from the operator. This paper will describe the construction of the robot and the use of microgravity technology to locate subsurface voids with the robot.

We present the design and initial results of a power-autonomous planar monopedal robot. The robot is a gasoline powered, two degree of freedom robot that runs in a circle, constrained by a boom. The robot uses hydraulic Series Elastic Actuators, force-controllable actuators which provide high force fidelity, moderate bandwidth, and low impedance. The actuators are mounted in the body of the robot, with cable drives transmitting power to the hip and knee joints of the leg. A two-stroke, gasoline engine drives a constant displacement pump which pressurizes an accumulator. Absolute position and spring deflection of each of the Series Elastic Actuators are measured using linear encoders. The spring deflection is translated into force output and compared to desired force in a closed loop force-control algorithm implemented in software. The output signal of each force controller drives high performance servo valves which control flow to each of the pistons of the actuators. In designing the robot, we used a simulation-based iterative design approach. Preliminary estimates of the robot's physical parameters were based on past experience and used to create a physically realistic simulation model of the robot. Next, a control algorithm was implemented in simulation to produce planar hopping. Using the joint power requirements and range of motions from simulation, we worked backward specifying pulley diameter, piston diameter and stroke, hydraulic pressure and flow, servo valve flow and bandwidth, gear pump flow, and engine power requirements. Components that meet or exceed these specifications were chosen and integrated into the robot design. Using CAD software, we calculated the physical parameters of the robot design, replaced the original estimates with the CAD estimates, and produced new joint power requirements. We iterated on this process, resulting in a design which was prototyped and tested. The Monopod currently runs at approximately 1.2 m/s with the weight of all the power generating components, but powered from an off-board pump. On a test stand, the eventual on-board power system generates enough pressure and flow to meet the requirements of these runs and we are currently integrating the power system into the real robot. When operated from an off-board system without carrying the weight of the power generating components, the robot currently runs at approximately 2.25 m/s. Ongoing work is focused on integrating the power system into the robot, improving the control algorithm, and investigating methods for improving efficiency.

This paper presents the development of an advanced concept for a next generation military vehicle based on state of the art technologies. The vehicle's platform will be directly suitable for high mobility applications for instance: Special Forces missions, Marine reconnaissance missions, and commercial racing in events such as Bajas and the Paris - Dakar. The platform will be a 10000 -14000 lbs high-speed multi-purpose vehicle, designed for extreme off-road operation. A completely new suspension concept is expected to be developed and the new vehicle topology will accommodate a new generation hybrid-electric power train. The dynamic performance targets are 125 mph off-road and 0-60 in 7 seconds. The concept design will focus also on survivability mainly through the use of a new vehicle topology (herein referred to as "island") specifically designed to enhance crew protection. The "island" topology consists in locating the powertrain and other vehicle equipment and subsystems around the crew compartment. Thus, even in the event of an external shield penetration the crew compartment remains protected by the surrounding equipment which serves in an additional role as a secondary shield. The paper presents vehicle specifications, performance capabilities, simulation models and virtual models of the vehicle.

Report progress of Payload Weaponry standards within the Joint Architecture for Unmanned Systems Weapons Payload Subcommittee.

The international community's focus on deterring terrorism has identified many vulnerabilities to a country's borders. These vulnerabilities include not only airports and rail lines but also the ports, harbors and miles of coastline which many countries must protect. In seeking to address this challenge, many technologies, processes and procedures have been identified that utilize single point or single source INT's (i.e., sources of intelligence - signals: SIGINT, imagery: IMINT, and open-source: INTERNET). These single source data sets include the information gleaned from shipping lines, port arrival and departure information and information from shipboard based electronic systems like the Automatic Identification System (AIS). Typically these are evaluated and incorporated into products or decisions in a singular manner and not with any reference or relationship to each other. In this work, an identification and analysis of these data sets will be performed in order to determine: •Any commonality between these data sets, •The ability to fuse information between these data sets, •The ability to determine relationships between these data sets, and •The ability to present any fused information or relationships in a timely manner In summary, the work served as a means for determining the data sets that were of the highest value and for determining the fusion method for producing a product of value. More work can be done to define the data sets that have the most commonality and thus will help to produce a fused product in the most timely and efficient manner.

Web Services are becoming the standard technology used to share data for many Navy and other DoD operations. Since Web Services technologies provide for discoverable, self-describing services that conform to common standards, this paradigm holds the promise of an automated capability to obtain and integrate data. However, automated integration of applications to access and retrieve data from heterogeneous sources in a distributed system such as the Internet poses many difficulties. Assimilation of data from Web-based sources means that differences in schema and terminology prevent simple querying and retrieval of data. Thus, machine understanding of the Web Services interface is necessary for automated selection and invocation of the correct service. Service availability is also an issue that needs to be resolved. There have been many advances on ontologies to help resolve these difficulties to support the goal of sharing knowledge for various domains of interest. In this paper we examine the use of case-based classification as an alternative/supplement to using ontologies for resolving several questions related to knowledge sharing. While ontologies encompass a formal definition of a domain of interest, case-based reasoning is a problem solving methodology that retrieves and reuses decisions from stored cases to solve new problems, and case-based classification involves applying this methodology to classification tasks. Our approach generalizes well in sparse data, which characterizes our Web Services application. We present our study as it relates to our work on development of the Advanced MetOc Broker, whose objective is the automated application integration of meteorological and oceanographic (MetOc) Web Services.

The reference spectral power responsivity scale of NIST is being extended from the silicon range to the infrared (IR) using pyroelectric radiometers. Two transfer standard pyroelectric radiometers have been developed at NIST. The main design consideration was to obtain only a minimal increase in the measurement uncertainty during the responsivity scale extension. Domain engineered LiNbO₃ and regular LiTaO₃ pyroelectric detectors were used in the two radiometers. Both detectors are gold-black coated and temperature controlled. Reflecting domes are attached to the radiometer inputs to decrease the reflectance loss and to improve the spatial uniformity of responsivity in the infrared. Four commercial pyroelectric detectors have been added to the group and used as working standards. The relative spectral responsivity of all pyroelectric detectors was determined from spectral reflectance measurements. The radiant power responsivity tie points were derived from Si trap and single element detectors traceable to the NIST reference responsivity scale. The pyroelectric radiometers have been characterized for frequency and temperature dependent responsivity, noise, spatial non-uniformity of responsivity, angular responsivity, and linearity. The expanded (relative) uncertainty of the spectral power responsivity calibrations ranged between 0.5 % and 1.2 % (k=2) within the 1 μm to 19 μm range.

Recent homeland security problems in various countries indicate that fixed surveillance systems at important places are not adequate enough. As the security threats take new dimensions in future, mobile smart security personnel wearing high-tech gear will form the basic infrastructure. See first, listen first, detect first, track first, communicate first with peers, assess the threat and coordinate with security head-quarters are the functions of high-tech gear. This paper proposes a high-tech gear involving (i) hands-free and obtrusion-free textile-based wearable microphone array to capture users voice and interface with body-worn computer, (ii) microphone arrays embedded in textiles to listen and record others voices from a distance, (iii) miniature cameras embedded in the shirt to provide the user with omni vision (iv) wireless personal display as GUI hidden in textile or natural glasses, (v) GPS and body area network for positional awareness for information in the form of text or textile integrated, (vi) reconfigurable HW/SW for all the above functions configured in the form of a usual belt. The main focus of this paper is how to configure the high-tech gear with all these sophisticated functions to disappear into the natural wearables of the user giving him normal look in the public. This project is sponsored by Defence Science & Technology Agency, Ministry of Defence, Singapore. This paper covers multi-discipline technologies at system level, hence not possible to go into details of any subsystem. The main objective of this paper is to share our thoughts and get feedback. Progress and some critical design issues are discussed in this paper.

Homeland security and defense applications seek to reduce the risk of undesirable eventualities across physical space in real-time. With that functional requirement in mind, our work focused on the development of IP based agent telecommunication solutions for heterogeneous sensor / robotic intelligent "Things" that could be deployed across the internet. This paper explains how multi-organization information and device sharing alliances may be formed to enable organizations to act as agents of homeland security (in addition to other uses). Topics include: (i) using location-aware, agent based, real-time information sharing systems to integrate business systems, mobile devices, sensor and actuator based devices and embedded devices used in physical infrastructure assets, equipment and other man-made "Things"; (ii) organization-centric real-time information sharing spaces using on-demand XML schema formatted networks; (iii) object-oriented XML serialization as a methodology for heterogeneous device glue code; (iv) how complex requirements for inter / intra organization information and device ownership and sharing, security and access control, mobility and remote communication service, tailored solution life cycle management, service QoS, service and geographic scalability and the projection of remote physical presence (through sensing and robotics) and remote informational presence (knowledge of what is going elsewhere) can be more easily supported through feature inheritance with a rapid agent system development methodology; (v) how remote object identification and tracking can be supported across large areas; (vi) how agent synergy may be leveraged with analytics to complement heterogeneous device networks.

The rapid dissemination of information to both the warfighter and analyst is critical on the modern battlefield. In addition, the tools used to analyze and display the information must be accurate, reliable, and consistent, independent of the platform, or deployment methodology currently being used. Displayed information includes raw sensor data, processed/fused sensor data, results of analysis, friendly force location and status, local context, and a variety of other data. This document presents a software architecture that is capable of displaying information in a consistent fashion across a number of application architectures, deployment scenarios, and target devices.

An important element for the fielding of a viable, effective NATO Response Force (NRF) is access to meteorological, oceanographic, geospatial data (GEOMETOC) and imagery. Currently, the available GEOMETOC information suffers from being very fragmented. NATO defines the Recognised Environmental Picture as controlled information base for GEOMETOC data. The NATO REP proposes an architecture that is both flexible and open. The focus lies on enabling a network-centric approach. The key into achieving this is relying on using open, well recognized standards that apply to both the data exchange protocols and the data formats. Communication and information exchange based on open standards enables system interoperability. Diverse systems, each with unique, specialized contributions to an increased understanding of the battlespace, can now cooperate to a manageable information sphere. By clearly defining responsibilities in the generation of information, a reduction in data transfer overhead is achieved . REP identifies three main stages in the dissemination of GEOMETOC data. These are Collection, Fusion (and Analysis) and Publication. A REP architecture has been successfully deployed during the NATO Coalition Warrior Interoperability Demonstration (CWID) in Lillehammer, Norway during June 2005. CWID is an annual event to validate and improve the interoperability of NATO and national Consultation and command, control, communications, computers, intelligence, surveillance, and reconnaissance (C4ISR) systems. With a test case success rate of 84%, it was able to provide relevant GEOMETOC support to the main NRF component headquarters. In 2006, the REP architecture will be deployed and validated during the NATO NRF Steadfast live exercises.

Speech Recognition systems, historically, have proven to be cumbersome and insufficiently accurate for a range of applications. The ultimate goal of our proposed technology is to fundamentally change the way current Speech Recognition (SR) systems interact with humans and develop an application that is extremely hardware efficient. Accurate SR and reasonable hardware requirements will afford the average first responder officer, e.g., police officer, a true break-through technology that will change the way an officer performs his duties. The presented technology provides a cutting-edge solution for human-machine interaction through the utilization of a properly solved Wake-Up-Word (WUW) SR problem. This paradigm-shift provides the basis for development of SR systems with truly "Voice Activated" capabilities, impacting all SR based technologies and the way in which humans interact with computers. This shift is a radical departure from the current "push-to-talk" paradigm currently applied to all speech-to-text or speech-recognition applications. To be able to achieve this goal, a significantly more accurate pattern classification and scoring technique is required, which in turn provides SR systems enhanced performance for correct recognition (i.e., minimization of false rejection) as well as correct rejection (i.e., minimization of false acceptance). A revolutionary and innovative classification and scoring technique is used that is a significant enhancement over an earlier method presented in reference [1]. The solution in reference [1] has been demonstrated to meet the stringent requirements of the WUW-SR task. Advanced solution of [1] is a novel technique that is model and algorithm independent. Therefore, it could be used to significantly improve performance of existing recognition algorithms and systems. Reduction of error rates of over 40% are commonly observed for both false rejections and false acceptance. In this paper the architecture of the WUW-SR based system as interface to current SR applications is presented. In this system WUW-SR is used as a gateway for truly Voice Activated applications utilizing the current solution without "push-to-talk" paradigm. The technique has been developed with hardware optimization in mind and therefore has the ability to run as a "background" application on a standard Windows-based PC platform.

Protection of the Nation's borders in the post-911 era has taken on increased importance while it has become more technically challenging due to dramatic increases in the number of illegal aliens attempting unauthorized border crossings. Unattended ground sensors, used in large numbers, have been a key element of the US Border Patrol's inventory of sensing systems that are deployed along the borders to alert agents to intrusions. The legacy sensors are based upon decades old technology and limited in their ability to be networked and integrated into a cohesive web that can provide timely information that can be readily integrated into the Border Patrol and DHS information networks. This paper presents an introduction to a system developed by McQ for border monitoring and intrusion detection that provides full networked capability, from the sensor to the display. The paper also includes results of testing and integration with DHS information systems. The significance of Internet protocol based information generation at the sensor level and real time distribution of data is emphasized, including resource and infrastructure sharing and scalability to nationwide scope will also be discussed.

The technical concept for this project has existed since the Chernobyl accident in 1986. A host of Eastern European nations have developed countrywide grid of sensors to monitor airborne radiation. The objective is to build a radiological sensor network for real-time monitoring of environmental radiation levels in order to provide data for warning, and consequentially the assessment of a nuclear event. A network of radiation measuring equipment consisting of gamma, neutron, alpha, and beta counters would be distributed over a large area (preferably on fire station roof tops) and connected by a wireless network to the emergency response center. The networks would be deployed in urban environments and would supply first responders and federal augmentation teams (including those from the U.S. Departments of Energy, Defense, Justice, and Homeland Security) with detailed, accurate information regarding the transport of radioactive environmental contaminants, so the agencies can provide a safe and effective response. A networked sensor capability would be developed, with fixed sensors deployed at key locations and in sufficient numbers, to provide adequate coverage for early warning, and input to post-event emergency response. An overall system description and specification will be provided, including detector characteristics, communication protocols, infrastructure and maintenance requirements, and operation procedures. The system/network can be designed for a specifically identified urban area, or for a general urban area scalable to cities of specified size. Data collected via the network will be transmitted directly to the appropriate emergency response center and shared with multiple agencies via the Internet or an Intranet. The data collected will be managed using commercial off - the - shelf Geographical Information System (GIS). The data will be stored in a database and the GIS software will aid in analysis and management of the data. Unique features of the system include each node being assigned a health-effect based risk factor. By connecting the nodes on a particular measured isopleth one can define the plume accurately. Radon counts will be provided and used to calculate the alpha counts. The radiological data collected will also be of value under routine conditions, in the absence of a radiological threat, to provide a detailed map of radiation background in the urban environment and complement predictive models of radiation transport. The data can be transferred to the National Atmospheric Release Advisory Center (NARAC) to augment its predictive model, thereby increasing its fidelity. Initially, as a proof of concept, a few nodes will be built for the purpose of demonstrating the concept.

We have designed and constructed a magnetic gradiometer for underwater mine detection, location and tracking. The United States Naval Surface Warfare Center (NSWC PC) in Panama City, FL has conducted sea tests of the system using an unmanned underwater vehicle (UUV). The Real-Time Tracking Gradiometer (RTG) measures the magnetic field gradients caused by the presence of a mine in the Earth's magnetic field. These magnetic gradients can then be used to detect and locate a target with the UUV in motion. Such a platform can also be used for other applications, including the detection and tracking of vessels and divers for homeland (e.g., port) security and the detection of underwater pipelines. Data acquired by the RTG in sea tests is presented in this paper.

Seismic detection systems for homeland defense and security applications are an important additional layer to perimeter, border and zone protection. General Sensing Systems has been developing a novel method and corresponding software for footstep detection with a near zero false alarm rate. This method has been realized in a number of detection systems. The testing of the GSS seismic systems in various environment noise conditions showed that such systems can be successfully used for other target detection. Such "unconventional" targets can include light and heavy vehicles, trains, helicopters and ships. This paper describes the signal characteristics of such targets and the preliminary experimental data on the corresponding detection range. We also report on the seismic sensor and seismic system requirements for target detection.

Acoustic sensing systems are used to detect, localize, track and classify sources of military interest in real time with negligible false alarm rates. Automated acoustic systems are able to cue response systems and devices such as cameras for source identification. Two defense applications are demonstrated: one involves remote land-based surveillance where an array of unattended passive acoustic ground sensors automatically cues a day/night camera to observe the passage of ground vehicles, the landing of air vehicles on an isolated air strip, and the transit of motor-powered watercraft in estuarine waters. The video imagery is compressed and relayed via satellite to a central monitoring facility for input to the decision and intelligence processes. The other application is for in-harbor force protection and port infrastructure security where a high-frequency high-resolution monostatic active sonar automatically detects, localizes and tracks fast inshore surface watercraft in real time. A cavitating propeller forms a bubble wake that lasts several minutes and is highly reflective of the incident sonar energy. The wake, which traces the trajectory of the watercraft, is clearly delineated on the sonar display. The active sonar reliably estimates the instantaneous position of the moving source at each point along its path of travel. The sonar can be used to pan an imaging device to aid identification of the moving source or to vector autonomous response craft for intercept purposes.

In order to resolve multiple closely spaced sources moving in a tight formation using unattended acoustic sensors, the array aperture must be extended using a sparse array geometry. Traditional sparse array algorithms rely on the spatial invariance property often leading to inaccurate Direction of Arrival (DOA) estimates due to the large side-lobes present in the power spectrum. Many problems of traditional sparse arrays can be alleviated by forming a sparse array using randomly distributed single microphones. The power spectrum of a random sparse array will almost always exhibit low side-lobes, thus increasing the ability of the beamforming algorithm to accurately separate and localize sources. This paper examines the robustness of randomly distributed sparse array beamforming in situations where the exact sensor location is unknown and benchmark its performance with that of traditional baseline sparse arrays. A realistic acoustic propagation model is also used to study fading effects as a function of range and its influence on the beamforming process for various sparse array configurations.

False alarms from individual sensors and duplicate detections from sensors in close proximity provide a user with inaccurate and superfluous information. Responding to all of these detections distracts the user, and also wastes system resources including bandwidth and storage capacity. Fusion can reduce these implications of an unattended sensor system and can occur on three different levels: multi-modal fusion of multiple transducer-based algorithms (including PIR, magnetic, seismic, acoustic, video, and biological/chemical) within a single remote ground sensor to provide a single detection; multi-sensor fusion which combines the detections of several remote ground sensors in a network; and multi-resource fusion which combines multi-modal and multi-sensor fusion with other resources such as historical, media, statistical, and user-defined information. Each level of fusion may be used together or separately to allow for increased sensitivity and a low false alarm rate while conserving power, bandwidth, storage capacity, and user interaction. This paper will describe the design and usage of each level of fusion in a networked unattended ground sensor system.

In this age of global terrorism the ability to detect nuclear material (i.e., radioactive sources) at border crossings is of great importance. Today radiation sensing devices range from handheld detectors to large ultra high-resolution gamma-ray spectrometers. The latter are stationary devices and often used in the form of "portals" placed at border crossings. Currently, border crossings make use of these radiation portals as isolated passive devices. A threshold is set on each detector and any time that threshold is reached an alarm is triggered. Once an alarm is triggered it is assumed that first responders with handheld detectors will disperse in order to determine the location of the radioactive source. This manner of locating a threat is highly dependent upon the reaction of the first responders, thus causing unpredictable delays. We seek to better automate the identification of radioactive sources, by using sensor fusion algorithms which combine the data from multiple sensors (radioactive, RFID, vision) to deduce the location of the source. These algorithms capitalize upon the geometry of a "typical" border crossing layout where parallel lines of vehicles or people are queued so that the location can be computed in near real-time. We find that source location is quickly computable, using using as few as one sensitive radioactive detector, augmented by a visual or RFID tracking system.

The necessity to control certain areas from outside intrusion or, vice versa, preventing subjects/objects (e.g. prisoners) from leaving a controlled area has brought to life numerous designs of surveillance systems for the above-mentioned tasks. Fibers, laser beams, microwaves, etc have been used for decades to provide an alarm signal, should anyone or anything cross a light, radio beam or break a fiber. However, it is difficult to distinguish a stray animal from a human being, or even a snow ball from the first two using the conventional surveillance designs. False alarms render practically useless the above means, especially for field applications. It is possible, nonetheless, to set up an automatic system that discriminates objects/subjects crossing the control line/perimeter - a statistical approach which includes time series analysis is proposed as a solution for the problem.

Planning Systems Incorporated (PSI) has been working with the National Institute of Justice, Center for Society Law and Justice (CSLJ) at the University of New Orleans, and law enforcement agencies in five highly varied United States locations to evaluate the use of an automated, wireless acoustic gun fire detection and localization system. Multiple SECURES(r) systems have been deployed and are in operation around the county. The most recent SECURES(r) implementation has been with the Newport News VA Police Department (NNPD) and East Orange NJ Police Department (EOPD). This paper will discuss successes and specific examples of its use by law enforcement to solve crimes and reduce community gunfire.

Feature extraction methods based on the discrete wavelet transform and multiresolution analysis facilitate the development of a robust classification algorithm that reliably discriminates between launch and impact mortar events via acoustic signals produced during these events. Distinct characteristics arise within the different explosive events because impact events emphasize concussive and shrapnel effects, while launch events result from blasts that expel and propel a mortar round from a gun. The ensuing blast waves are readily characterized by variations in the corresponding peak pressure and rise time of the waveform, differences in the ratio of positive pressure amplitude to the negative amplitude, variations in the prominent frequencies associated with the varying blast events and variations in the overall duration of the resulting waveform. Unique attributes can also be identified that depend upon the properties of the gun tube, projectile speed at the muzzle, and the explosive/concussive properties associated with the events. In this work, the discrete wavelet transform is used to extract the predominant components of these characteristics from the acoustic signatures of the event at ranges of 1km. Highly reliable discrimination is achieved with a feedforward neural network classifier trained on a feature space derived from the distribution of wavelet coefficients and higher frequency details found within different levels of the multiresolution decomposition. We show that the algorithms provide a reliable discrimination (>97%) between launch and impact events using data collecting during several separate field test experiments.

The Early Attack Reaction Sensor (EARS) is a modified passive acoustic system that detects gunshots (muzzle blast and/or shockwave) to provide the user with relative azimuth and range of sniper fire via both audio alert and visual display. The EARS system consists of a microphone array in a small planar configuration and an equivalently sized Digital Signal Processing board, which is interfaced to a PDA via a PCMCIA slot. Hence, configuration easily provides portability. However, the system is being repackaged for man-wearable and vehicle mount applications. The EARS system in a PDA configuration has been tested in open fields at up to 500 meters range and has provided useable bearing and range information against the sniper rounds. This paper will discuss EARS system description, various test results, and EARS system capabilities and limitations.

Free Space Optics (FSO) through cloud has lately attracted substantial attention for a variety of applications[1][2]. FSO is a promising candidate for emerging broadband applications, considering that RF spectrum is already congested, rendering assignment of additional RF channels costly. Combining the attributes of a higher data rate but bursty link (FSO) with the attributes of a lower data rate but reliable link (RF) can yield attributes better than either one alone, enabling a high availability link at high data rates. This transmission configuration is typically called a hybrid RF/FSO wireless system [3][4]. Recently, there have been interests in filterbank transceivers, and both OFDM and wavelet modulation technologies can be understood as examples. In FSO, normally we are given huge optical bandwidth, but in fact, use of the huge bandwidth is limited due to both enabling technologies and the severe channel distortion. Therefore, not only in RF but also in FSO, we also need efficient use of resources. In this research, we aim at the following goals. First, wavelet packet modulation (WPM) will be applied to FSO to find the resource-efficient optimal spectral decomposition of the optical channel. Then, equalization will be applied to further enhance FSO performance.

The Spaceborne Scanning Lidar System (SSLS) system is a space-qualified scanning lidar system developed by MDA and Optech. It has been operating on orbit since April 2005 as part of the XSS-11 one-year demonstration of space technologies associated with spacecraft autonomous rendezvous and proximity operations. The SSLS has already successfully supported long and medium-range object acquisition and tracking. Short range acquisition, tracking, and imaging tasks are scheduled towards the end of its one-year mission. MDA and Optech view SSLS as the first 'smart' product in the RELAVIS line of scanning lidar products. An upgrade plan, addressing customer needs and lessons learned during SSLS build and operation on orbit, has been established and is currently being implemented. Next generation SSLS lidar will provide improved performance and real-time space object tracking solution based on point cloud data acquired by the lidar. Real-time pose (position and orientation) capability will be provided in addition to the currently provided range, bearing, and centroid telemetry data. The integrated pose solution will provide the user with tracking data while reducing spacecraft databus and processor utilization. This new functionality expands the SSLS role from a 'sensor only' ranging role to a robust long/medium and short range 'ranging and tracking solution' supporting rendezvous and close proximity missions. This paper describes the SSLS upgrade plan and provides information related to the implementation and progress of the upgrade via test results of the new SSLS capabilities.

The awareness of terrorists covertly transporting chemical warfare (CW) and biological warfare (BW) agents into government, military, and civilian facilities to harm the occupants has increased dramatically since the attacks of 9/11. Government and civilian security personnel have a need for innovative surveillance technology that can rapidly detect these lethal agents, even when they are hidden away in sealed containers and concealed either under clothing or in hand-carried items such as mailed packages or handbags. Sensor technology that detects BW and CW agents in mail or sealed containers carried under the clothing are under development. One promising sensor technology presently under development to detect these threats is active millimeter-wave holographic radar imaging, which can readily image concealed items behind paper, cardboard, and clothing. Feasibility imaging studies at frequencies greater than 40 GHz have been conducted to determine whether simulated biological or chemical agents concealed in mail packages or under clothing could be detected using this extremely high-frequency imaging technique. The results of this imaging study will be presented in this paper.

Ship on ocean may be distorted for some reasons. Detecting its obliquity of distortion in time is helpful for controlling its pose. A scheme is presented in the article, which can match the practical precision and speed requirement of measurement. Practical formula and arithmetic are brought forward. Theoretical discussion, experimentation, and emulation are introduced to indicate their feasibility.

High Speed Multi-Channel Fiber-Optic Transmitter (Tx) and Receiver (Rx) modules have been developed for Next Generation Ground Vehicle Applications. These fiber-optic multi-channel modules take advantage of the high speeds (10 Gb/Sec/Channel) and have the ability to connect multiple sensors and systems using a rugged fiber-optic cable capable of working with very high data rates for real time information. In this paper we present design, development and application of these high Speed modules for Tethered Robotic Applications. We will present design, development and performance results for 12 channels - Tx and Rx fiber-optic module capable of providing 120 Gb/Module operations for Army's Manned and Unmanned Vehicle Applications. This technology enables the application of very high data rates and multiple channels of real time, high-resolution visible and thermal IR streaming video that enhances the ability for real time information without any bandwidth limitations.

We use a radio-frequency (RF) diode laser modulation technique to interrogate a fiber Fabry-Perot (FFP), and demonstrate unprecedented remote sensitivity performance for measuring fiber dynamic strain. We present results for its experimental demonstration in a 5 km remote strain sensing system, where we have attained sub-picostrain/√Hz resolution in an acoustic signal band from 100 Hz to 100 kHz, with better than 300 femtostrain/√Hz sensitivity above 300 Hz. This is unprecedented in sensitivity and broadband performance, unparalleled over such a long interrogation distance. Strain signals are extracted interferometrically from the differential phase between the carrier and its RF sidebands. This elegant architecture is immune to intensity noise in the laser, as well as ambient acoustic and mechanical perturbations in the remote delivery fiber. The excellent frequency discrimination by the FFP also facilitates a superior signal-to-noise ratio, to effectively overcome the random phase noise due to Rayleigh backscatter in the long length of fiber. Furthermore, the interrogation length can be well beyond the coherence length of the laser source. We show that this performance is limited only by the frequency noise of the diode laser source, as all systemic noise sources in the delivery fiber are effectively transparent to the sensing architecture. This remote sensitivity is a seminal demonstration for a range of applications, such as sea floor acoustic sensing arrays, deep sea hydrophone arrays, and remote surveillance. We will discuss upscaling of this single element experiment to multi-element sensing arrays.

An in-ground perimeter security system has been developed by the Naval Undersea Warfare Center Division Newport based upon fiber optic sensor technology. The system, called Blue Rose, exploits the physical phenomenon of Rayleigh optical scattering, which occurs naturally in optical fibers used traditionally for Optical Time Domain Reflectometry techniques to detect sound and vibration transmitted by intruders such as people walking or running and moving vehicles near the sensor. The actual sensor is a single-mode optical fiber with an elastomeric coating that is buried in the ground. A long coherence length laser is used to transmit encoded light down the fiber. Minute changes in the fiber in response to the intrusion produce phase changes to the returning backscattered light signal. The return light signal contains both the actual intrusion sound and the location information of where along the fiber the intrusion has occurred. A digital, in-ground, Blue Rose system has been built and is now operational at NUWC. Due to the low cost of the optical fiber sensor and unique benefits of the system, the Blue Rose system provides an advantage in long perimeter or border security applications and also reduces security manning requirements and therefore overall cost for security.

A multitude of scientific, medical, and defense applications require imaging at low light level. Examples include: live-cell fluorescence microscopy, wavefront sensing for adaptive optics, and night vision. To address these applications low light level sensors need to have low noise, high quantum efficiency, low lag, high MTF, high frame rates, and low power. Over the past 50 years a variety of techniques have been developed to analyze and compare these technologies. The purpose of this paper is to develop an analytical method for estimating limiting resolution of low light level sensors and cameras. We present a communication theory based model that is designed to enable rapid evaluation of low light level sensors and aid in the understanding of how these systems operate. This model can be applied to electron multiplied CCDs, electron bombarded CMOS sensors, and hybrid CCD/CMOS sensors. In addition we also describe a device physics based low light level camera simulator. We compare our model to the camera simulator and show that the model can be used to accurately predict camera performance. In addition the computational complexity of our model is 1/150 of a complete low light level camera simulator.

Airborne surveillance helicopters and aeroplanes used by security and defence forces around the world increasingly rely on their visible band and thermal infrared cameras to prosecute operations such as the co-ordination of police vehicles during the apprehension of a stolen car, or direction of all emergency services at a serious rail crash. To perform their function effectively, it is necessary for the airborne officers to unambiguously identify police and the other emergency service vehicles. In the visible band, identification is achieved by placing high contrast symbols and characters on the vehicle roof. However, at the wavelengths at which thermal imagers operate, the dark and light coloured materials have similar low reflectivity and the visible markings cannot be discerned. Hence there is a requirement for a method of passively and unobtrusively marking vehicles concurrently in the visible and thermal infrared, over a large range of viewing angles. In this paper we discuss the design, detailed angle-dependent spectroscopic characterisation and operation of novel visible and infrared vehicle marking materials, and present airborne IR and visible imagery of materials in use.

We report the preparation of explosives nanoparticles of RDX and TNT in a variety of substrates that include glass, silicon and stainless steel. The explosive nanoparticles were prepared by means of pneumatically assisted nebulization (PAN) using an electrospray (ESI) needle, which allowed for the direct deposit of the energetic material onto the substrate. The deposited nanoparticles were characterized by optical microscopy, Scanning Electron Microscopy (SEM), Energy Dispersive X-ray analysis (EDX) and Raman Microscopy. SEM micrographs showed that the process produced particles with a mean size in the range of 80-500 nm and a narrow size distribution. For TNT, the process produced smaller particles with a narrower size distribution. The EDX spectrum showed the presence of carbon, nitrogen and oxygen consistent with the elemental composition of the energetic materials. The chemical properties of the nanoparticles were also determined by vibrational spectroscopy.

Fourier Transform Infrared Spectroscopy coupled to Grazing Angle Probe and operating in Reflection Absorption Infrared Spectroscopy mode has been demonstrated that can be used as a potential technique to develop new methodologies for detection of explosives on surfaces in Phase I of this research. The methodology is remote sensed, in situ and can detect nanograms of most target compounds. It is solvent free technique and requires no sample preparation. In this work detection of traces of neat explosives and lab made mixtures equivalent to the important explosive formulation Pentolyte has been addressed. The sample set consisted of TNT, PETN and Pentolyte mixture present in various loading concentrations. The spectral data collected was subjected to a number of statistical pre-treatment methods, including first derivative and normalization transformations to make the data more suitable for analysis. Principal Component Analysis combined with Linear Discriminant Analysis was used to classify and discriminate the target analytes.

Peroxide-based explosives have become of increased interest mainly because they are easily prepared and are not detected by traditional detection devices. The thermal behavior of triacetone triperoxide (TATP), a cyclic peroxide explosive was characterized by Differential Scanning Calorimetry (DSC) and Thermal Gravimetric Analysis (TGA). Dynamic and isothermal methods were used to characterize the sublimation process and to measure the vapor pressure at a temperature range under exothermic decomposition. The enthalpy of sublimation and kinetic parameters were estimated from direct mass loss rate measurements. Melting point, decomposition temperature and enthalpies of transitions were determined and compared to other known materials. The values were also compared to other recently reported values. The results of this study will help in the development of standoff detection technologies for improvised explosive devices using peroxide based materials.

A method to prepare metallic nanoparticles films in the presence of a hydrophilic copolymer with the aim of inhibiting the formation of clusters in the nanoparticles has been developed. Thin films prepared could be used in applications such as sensors development and substrates for surface-enhanced Raman spectroscopy. The synthesis of colloidal solutions of silver nanoparticles was achieved by the reduction AgNO₃ using sodium citrate with thermal treatment which results in a robust fabrication of gold and silver films. The polymeric films were prepared by polymerization 2-hydroxyethyl methacrylate with methacrylic acid (method 1). The other procedure employed (method 2) incorporated the use of polyvinyl pyrrolidone and polyethylene glycol as copolymers. A scanning electron microscope was used to provide microstructural information of coverage achieved. The ability to tune the nanocoating structure and spectral and electronic properties can be used for applications such as sensors used in the detection of explosives. Silver nanoparticles were also characterized by surface-enhanced Raman scattering (SERS), which integrates high chemical sensitivity with spectroscopic identification and has enormous potential for applications involving ultra-sensitive chemical detection. Spectra were obtained using a Renishaw RM2000 Raman Microspectrometer system operating in the visible region excitation (532 nm).

Cyclic organic peroxides are sensitive to the presence of water and other contaminants that can deactivate the substance or make it less sensitive to chock, spark or other detonating mechanism. In the case of radiation such as laser action the opposite seems to happen, making the peroxides more sensitive to laser breakdown and local burning. In recent studies, TATP has been induced to sublimate faster during Raman analysis when it had contaminants or water, however, some studies have shown that TATP does not reacts when it is wet. This study is focused on determining if the presence of water and other contaminants affects peroxide stability and the detection by current technologies, such as IMS and vibrational spectroscopy. During the study, TATP and HMTD have been synthesized by different methods using certified chemicals and common household products. The research also focused on the effect of metal salts in the syntheses and the effect of temperature in the composition of the products. Differences in the location, shape, relative intensity, and in some cases appearance of new bands possibly due to Redox and complex formation reactions were evident. Bands corresponding to ν(O-O), ν(C-O), δ(CH₃-C) and δ(C-O) were located and assigned for Raman and IR spectroscopies.

Synthesis and characterization of hexamethelene triperoxide diamine (HMTD), tetramethylene diperoxide dicarbamide (TMDD) and tetramethylene diperoxide acetamide (TMDA) using GC-MS, HPLC-MS, FT-IR and Raman Microscopy has been carried out. The study also centered in the synthesis and characterization of other cyclic amine peroxides, including and different forms of caged peroxides from other diaminoalkanes. Interest also was given to the secondary products of all syntheses and the effect of temperature in the composition mixtures of the preparations. Differentiation spectroscopy and spectrometry studies were also conducted. In these studies the differences in the ν(O-O), ν(N-C), ν(N-H), ν(C-O), δ(CH₃-C) and δ(C-O) bands for Raman and IR were established. For the GC/MS spectrometric studies retention times and fragmentation patterns for GC-MS and GC-FT-IR useful in amine peroxide differentiation were also established.

The cyclic nitramine hexahydro-1,3,5-trinitro-s-triazine, commonly known as RDX, is a powerful secondary explosive that has attracted considerable attention due to its polymorphism. The conformers of RDX are distinguished mainly by the arrangement of the nitro groups relative to the ring atoms of the RDX molecule. FTIR and Raman spectra of solid RDX and ¹³C enriched RDX are presented and assigned with the help of the density functional theory calculations. Chemical shielding constants were computed by gauge independent atomic orbital method (GIAO) for β-RDX conformer. The data are compared with the experimental solid and solution data, focusing on the agreement the spectral patterns and spectral trends. The results of harmonic vibrational frequencies and absolute shielding (GIAO) calculations using density functional theory approximation supported by experimental studies are reported. The qualitative agreement between the experimental and calculated values of the chemical shifts shed more light on the understanding the basic shift-molecular structure relationship of RDX conformers.

Au/Ag and Ag/Ag alloy surface roughened consisting of various mole fractions of gold and silver have been synthesized in aqueous solution by the co-reduction of chlorauric acid (HAuCl) and silver nitrate (AgNO₃) with trisodium citrate. For the metallic alloys it was found that the maximum of the plasmon band shifts linearly towards the blue with increasing silver content. Metal nanoparticles could be used in applications such specificity sensors and substrates for Enhanced Raman Spectroscopy (ERS). A goal in the emerging field of nanotechnology is to make nanostructures or nanoarrays with a very large surface area. Crystalline SnO₂ and Sc₂O₃ were also used for ERS experiments. Tin (IV) oxide is widely applied as a sensor component as a consequence of the high sensitivity of its conductivity to the surrounding atmosphere. Scandium oxide has been used for high reflectance coatings for UV applications. Nanoparticles were characterization by UV-VIS Spectroscopy and Scanning Electron-Microscopy (SEM). The SEM has been used to provide microstructural information of coverage used. Nanoparticle structure and spectral and electronic properties of these systems may allow for applications in sensors development for the use in nitroaromatic explosive detection at the subpicograms range.

Fourier transform infrared (FTIR) spectroscopy has been established as well suited for work outside the confinement of the sample compartment, provided the excitation source and the reflected light can be transported to the interferometer. Fiber optic cables that transmit in the Mid-IR range have made this possible by allowing the development of a series of spectroscopic probes for in situ analysis. In previous work it was established that surface concentrations of TNT as low as 0.3 μg/cm² (300 ng/cm²) could be detected with high confidence level. This detection limit varies according to macro properties. Properties such vapor pressure, physical adsorption, sublimation rate and surface-adsorbate thermodynamics can influence the detection limit. A close relation between vapor pressure and limit detection is shown for nitroexplosives. The amount of explosive and the residence time on stainless steel depends on this property, because at low surface concentrations the explosive goes to the vapor phase fast. Loading concentrations near the limits of detection were prepared and spectra were recorded at different temperatures in the range of 14-30°C. The nitro band was monitored for the experiments and the data was analyzed by using peak areas and Chemometrics. A close relationship between the detection limit and temperature was observed.