This PDF file contains the front matter associated with SPIE Proceedings Volume 9838 including the Title Page, Copyright information, Table of Contents, Introduction, and Conference Committee listing.

In this paper, a hybrid Monte Carlo Gauss mixture Kalman filter is proposed for the continuous orbit estimation problem. Specifically, the graphic processing unit (GPU) aided Monte Carlo method is used to propagate the uncertainty of the estimation when the observation is not available and the Gauss mixture Kalman filter is used to update the estimation when the observation sequences are available. A typical space object tracking problem using the ground radar is used to test the performance of the proposed algorithm. The performance of the proposed algorithm is compared with the popular cubature Kalman filter (CKF). The simulation results show that the ordinary CKF diverges in 5 observation periods. In contrast, the proposed hybrid Monte Carlo Gauss mixture Kalman filter achieves satisfactory performance in all observation periods. In addition, by using the GPU, the computational time is over 100 times less than that using the conventional central processing unit (CPU).

The goal of this research effort is to improve Space Domain Awareness (SDA) capabilities of current telescope systems through improved detection algorithms. Ground-based optical SDA telescopes are often spatially under-sampled, or aliased. This fact negatively impacts the detection performance of traditionally proposed binary and correlation-based detection algorithms. A Multiple Hypothesis Test (MHT) algorithm has been previously developed to mitigate the effects of spatial aliasing. This is done by testing potential Resident Space Objects (RSOs) against several sub-pixel shifted Point Spread Functions (PSFs). A MHT has been shown to increase detection performance for the same false alarm rate. In this paper, the assumption of a priori probability used in a MHT algorithm is investigated. First, an analysis of the pixel decision space is completed to determine alternate hypothesis prior probabilities. These probabilities are then implemented into a MHT algorithm, and the algorithm is then tested against previous MHT algorithms using simulated RSO data. Results are reported with Receiver Operating Characteristic (ROC) curves and probability of detection, P_d, analysis.

It is currently possible for space debris to remain undetected in close proximity to satellites. Current detection methods are adept at locating a single object in space, as well as two objects that are greatly separated, but have difficulty finding a second object that is nearby. The problem is exacerbated if the second object appears much dimmer than the first object. The method proposed in this paper would work with existing methods as an additional processing step that would process areas of astronomical images around places where objects are detected. In this case the proposed algorithm is designed to look at a pixel and determine how bright an object would be if there were an object there, then applies a binary hypothesis test to determine if an object is present. In theory, this will have the greatest advantage over existing methods when the objects are very close together or the second object is very dim. The algorithm has been tested on both simulated data and on a laboratory level test and improved the probability of detection by up to 300%.

Aperture synthesis imaging techniques using an interferometer provide a means to achieve imagery with spatial resolution equivalent to a conventional filled aperture telescope at a significantly reduced size, weight and cost, an important implication for air- and space-borne persistent observing platforms. These concepts have been realized in SIRII (Space-based IR-imaging interferometer), a new light-weight, compact SWIR and MWIR imaging interferometer designed for space-based surveillance. The sensor design is configured as a six-element Fizeau interferometer; it is scalable, light-weight, and uses structural components and main optics made of carbon fiber replicated polymer (CFRP) that are easy to fabricate and inexpensive. A three-element prototype of the SIRII imager has been constructed. The optics, detectors, and interferometric signal processing principles draw on experience developed in ground-based astronomical applications designed to yield the highest sensitivity and resolution with cost-effective optical solutions. SIRII is being designed for technical intelligence from geo-stationary orbit. It has an instantaneous 6 x 6 mrad FOV and the ability to rapidly scan a 6x6 deg FOV, with a minimal SNR. The interferometric design can be scaled to larger equivalent filled aperture, while minimizing weight and costs when compared to a filled aperture telescope with equivalent resolution. This scalability in SIRII allows it address a range of IR-imaging scenarios.

This paper presents an innovative approach to develop a Commercial Satellite Communications (COMSATCOM) service Technical Baseline (TB) and associated Program Baseline (PB) strategy using Portable Pool Bandwidth (PPBW) concept. The concept involves trading of the purchased commercial transponders’ Bandwidths (BWs) with existing commercial satellites’ bandwidths participated in a “designated pool bandwidth”³ according to agreed terms and conditions. Space Missile Systems Center (SMC) has been implementing the Better Buying Power (BBP 3.0) directive⁴ and recommending the System Program Offices (SPO) to own the Program and Technical Baseline (PTB) [1, 2] for the development of flexible acquisition strategy and achieving affordability and increased in competition. This paper defines and describes the critical PTB parameters and associated requirements that are important to the government SPO for “owning” an affordable COMSATCOM services contract using PPBW trading concept. The paper describes a step-by-step approach to optimally perform the PPBW trading to meet DoD and its stakeholders (i) affordability requirement, and (ii) fixed and variable bandwidth requirements by optimizing communications performance, cost and PPBW accessibility in terms of Quality of Services (QoS), Bandwidth Sharing Ratio (BSR), Committed Information Rate (CIR), Burstable Information Rate (BIR), Transponder equivalent bandwidth (TPE) and transponder Net Presence Value (NPV). The affordable optimal solution that meets variable bandwidth requirements will consider the operating and trading terms and conditions described in the Fair Access Policy (FAP).

Recently the U.S. Department of Defense (DOD) released the Defense Innovation Initiative (DII) [1] to focus DOD on five key aspects; Aspect #1: Recruit talented and innovative people, Aspect #2: Reinvigorate war-gaming, Aspect #3: Initiate long-range research and development programs, Aspect #4: Make DOD practices more innovative, and Aspect #5: Advance technology and new operational concepts. Per DII instruction, this paper concentrates on Aspect #2 and Aspect #4 by reinvigorating the war-gaming effort with a focus on an innovative approach for developing the optimum Program and Technical Baselines (PTBs) and their corresponding optimum acquisition strategies for acquiring future space systems. The paper describes a unified approach for applying the war-gaming concept for future DOD acquisition of space systems. The proposed approach includes a Unified Game-based Acquisition Framework (UGAF) and an Advanced Game-Based Mathematical Framework (AGMF) using Bayesian war-gaming engines to optimize PTB solutions and select the corresponding optimum acquisition strategies for acquiring a space system. The framework defines the action space for all players with a complete description of the elements associated with the games, including Department of Defense Acquisition Authority (DAA), stakeholders, warfighters, and potential contractors, War-Gaming Engines (WGEs) played by DAA, WGEs played by Contractor (KTR), and the players’ Payoff and Cost functions (PCFs). The AGMF presented here addresses both complete and incomplete information cases. The proposed framework provides a recipe for the DAA and USAF-Space and Missile Systems Center (SMC) to acquire future space systems optimally.

The Joint Space Operations Center (JSpOC) Mission System (JMS) is a service-oriented architecture (SOA) infrastructure with increased process automation and improved tools to enhance Space Situational Awareness (SSA) performed at the US-led JSpOC. The Advanced Research, Collaboration, and Application Development Environment (ARCADE) is a test-bed maintained and operated by the Air Force to (1) serve as a centralized test-bed for all research and development activities related to JMS applications, including algorithm development, data source exposure, service orchestration, and software services, and provide developers reciprocal access to relevant tools and data to accelerate technology development, (2) allow the JMS program to communicate user capability priorities and requirements to developers, (3) provide the JMS program with access to state-of-the-art research, development, and computing capabilities, and (4) support JMS Program Office-led market research efforts by identifying outstanding performers that are available to shepherd into the formal transition process. In this paper we will share with the international remote sensing community some of the recent JMS and ARCADE developments that may contribute to greater SSA at the JSpOC in the future, and share technical areas still in great need.

Thousands of space objects in the Earth orbital-region known as the GEO belt are categorized as debris. Relatively little is known about the thousands of space debris objects. Remote sensing techniques offer the only viable opportunity to learn more about these objects. In this paper an analysis is performed for observations using a hypothetical space-based multi-band infrared instrument to measure characteristics of GEO belt space debris. The purpose of this study is to understand the limitations of such an instrument and sensing modality for studying GEO belt space debris. Although certain aspects of this study are analytical, the results are anchored with results from the NASA-WISE experiments.

High resolution and wide-swath imaging can be obtained by Multiple-Input Multiple-Output (MIMO) synthetic aperture radar (SAR) with the state of the art technologies. The time division multiple access (TDMA) MIMO SAR mimics the motion of the antenna of SAR systems by switching the array channels to transmit the radar signals at different time slots. In this paper, we develop a simulation tool with ray tracing techniques to retrieve high resolution and accurate SAR images for development of MIMO SAR imaging methods. Without loss of generality, in the proposed simulator, we apply a TDMA MIMO SAR system with 13 transmitting antennas and 8 receiving antennas, where all transmitting antennas share a single transmitter and the receiving antennas share a single receiver. By comparing with the normal simulation MIMO SAR strategies, the simulation image using ray tracing results validate that the proposed method provides more accurate and higher resolution SAR images.

This paper presents a low size, weight and power – cost (SWaP-C) airborne sense and avoid (ABSAA) system, which is based on a linear frequency modulated continuous wave (LFMCW) radar and can be mounted on small unmanned aircraft system (UAS). The system satisfies the constraint of the available sources on group 2/3 UAS. To obtain the desired sense and avoid range, a narrow band frequency (or range) scanning technique is applied for reducing the receiver’s noise floor to improve its sensitivity, and a digital signal integration with fast Fourier transform (FFT) is applied to enhance the signal to noise ratio (SNR). The gate length and chirp rate are intelligently adapted to not only accommodate different object distances, speeds and approaching angle conditions, but also optimize the detection speed, resolution and coverage range. To minimize the radar blind zone, a higher chirp rate and a narrowband intermediate frequency (IF) filter are applied at the near region with a single antenna signal for target detection. The offset IF frequency between transmitter (TX) and receiver (RX) is designed to mitigate the TX leakage to the receiver, especially at close distances. Adaptive antenna gain and beam-width are utilized for searching at far distance and fast 360 degree middle range. For speeding up the system update rate, lower chirp rates and wider IF and baseband filters are applied for obtaining larger range scanning step length out of the near region. To make the system working with a low power transmitter (TX), multiple-antenna beamforming, digital signal integration with FFT, and a much narrower receiver (RX) bandwidth are applied at the far region. The ABSAA system working range is 2 miles with a 1W transmitter and single antenna signal detection, and it is 5 miles when a 5W transmitter and 4-antenna beamforming (BF) are applied.

Real-time information fusion based on WAMI (Wide-Area Motion Imagery), FMV (Full Motion Video), and Text data is highly desired for many mission critical emergency or security applications. Cloud Computing has been considered promising to achieve big data integration from multi-modal sources. In many mission critical tasks, however, powerful Cloud technology cannot satisfy the tight latency tolerance as the servers are allocated far from the sensing platform, actually there is no guaranteed connection in the emergency situations. Therefore, data processing, information fusion, and decision making are required to be executed on-site (i.e., near the data collection). Fog Computing, a recently proposed extension and complement for Cloud Computing, enables computing on-site without outsourcing jobs to a remote Cloud. In this work, we have investigated the feasibility of processing streaming WAMI in the Fog for real-time, online, uninterrupted target tracking. Using a single target tracking algorithm, we studied the performance of a Fog Computing prototype. The experimental results are very encouraging that validated the effectiveness of our Fog approach to achieve real-time frame rates.

Humans have always had a keen interest in understanding activities and the surrounding environment for mobility, communication, and survival. Thanks to recent progress in photography and breakthroughs in aviation, we are now able to capture tens of megapixels of ground imagery, namely Wide Area Motion Imagery (WAMI), at multiple frames per second from unmanned aerial vehicles (UAVs). WAMI serves as a great source for many applications, including security, urban planning and route planning. These applications require fast and accurate image understanding which is time consuming for humans, due to the large data volume and city-scale area coverage. Therefore, automatic processing and understanding of WAMI imagery has been gaining attention in both industry and the research community. This paper focuses on an essential step in WAMI imagery analysis, namely vehicle classification. That is, deciding whether a certain image patch contains a vehicle or not. We collect a set of positive and negative sample image patches, for training and testing the detector. Positive samples are 64 × 64 image patches centered on annotated vehicles. We generate two sets of negative images. The first set is generated from positive images with some location shift. The second set of negative patches is generated from randomly sampled patches. We also discard those patches if a vehicle accidentally locates at the center. Both positive and negative samples are randomly divided into 9000 training images and 3000 testing images. We propose to train a deep convolution network for classifying these patches. The classifier is based on a pre-trained AlexNet Model in the Caffe library, with an adapted loss function for vehicle classification. The performance of our classifier is compared to several traditional image classifier methods using Support Vector Machine (SVM) and Histogram of Oriented Gradient (HOG) features. While the SVM+HOG method achieves an accuracy of 91.2%, the accuracy of our deep network-based classifier reaches 97.9%.

In a distributed radar track fusion system, it is desired to limit the communication rate between the sensors and the central node to only the most relevant information available. One way to do this is to use some metric that judges quantity of new information available, in comparison to that which has already been provided. The J-Divergence is a symmetric metric, derived from the Kullback-Liebler divergence, which performs a comparison of the statistical distance between two probability distributions. For the comparison between new and old data, a large J-Divergence can represent the existence of new information, while a small J-Divergence represents the lack of new information. Previous work included an application where the J-Divergence was used to limit data for scenarios in which the primary state estimator was an Extended Kalman Filter and used only Gaussian approximations at the local sensors. This paper expands the range of estimators to particle filters in order to account for situations where censoring is desired to be applied to non-linear/non-Gaussian environments. A derivation of the J-Divergence between probability density functions (PDFs) which are approximated by particles is provided for use in a non-feedback fusion case. An example application is given involving a 2D radar tracking scenario using the J-Divergences of a particle filter with the Gaussian approximation and a particle filter with the approximated discrete prior/posterior PDFs.

With the explosive growth of network technologies, insider attacks have become a major concern to business operations that largely rely on computer networks. To better detect insider attacks that marginally manipulate network traffic over time, and to recover the system from attacks, in this paper we implement a temporal-based detection scheme using the sequential hypothesis testing technique. Two hypothetical states are considered: the null hypothesis that the collected information is from benign historical traffic and the alternative hypothesis that the network is under attack. The objective of such a detection scheme is to recognize the change within the shortest time by comparing the two defined hypotheses. In addition, once the attack is detected, a server migration-based system recovery scheme can be triggered to recover the system to the state prior to the attack. To understand mitigation of insider attacks, a multi-functional web display of the detection analysis was developed for real-time analytic. Experiments using real-world traffic traces evaluate the effectiveness of Detection System and Recovery (DeSyAR) scheme. The evaluation data validates the detection scheme based on sequential hypothesis testing and the server migration-based system recovery scheme can perform well in effectively detecting insider attacks and recovering the system under attack.

System state estimation in the presence of an adversary that injects false information into sensor readings has attracted much attention in wide application areas, such as target tracking with compromised sensors, secure monitoring of dynamic electric power systems, secure driverless cars, and radar tracking and detection in the presence of jammers. From a malicious adversary’s perspective, the optimal strategy for attacking a multi-sensor dynamic system over sensors and over time is investigated. It is assumed that the system defender can perfectly detect the attacks and identify and remove sensor data once they are corrupted by false information injected by the adversary. With this in mind, the adversary’s goal is to maximize the covariance matrix of the system state estimate by the end of attack period under a sparse attack constraint such that the adversary can only attack the system a few times over time and over sensors. The sparsity assumption is due to the adversary’s limited resources and his/her intention to reduce the chance of being detected by the system defender. This becomes an integer programming problem and its optimal solution, the exhaustive search, is intractable with a prohibitive complexity, especially for a system with a large number of sensors and over a large number of time steps. Several suboptimal solutions, such as those based on greedy search and dynamic programming are proposed to find the attack strategies. Examples and numerical results are provided in order to illustrate the effectiveness and the reduced computational complexities of the proposed attack strategies.

This paper describes a technical approach for the development of RFI prediction models using carrier synchronization loop when calculating Bit or Carrier SNR degradation due to interferences for (i) detecting narrow-band and wideband RFI signals, and (ii) estimating and predicting the behavior of the RFI signals. The paper presents analytical and simulation models and provides both analytical and simulation results on the performance of USB (Unified S-Band) waveforms in the presence of narrow-band and wideband RFI signals. The models presented in this paper will allow the future USB command systems to detect the RFI presence, estimate the RFI characteristics and predict the RFI behavior in real-time for accurate assessment of the impacts of RFI on the command Bit Error Rate (BER) performance. The command BER degradation model presented in this paper also allows the ground system operator to estimate the optimum transmitted SNR to maintain a required command BER level in the presence of both friendly and un-friendly RFI sources.

This paper investigates weather effects on a satellite communication (SATCOM) link communication channel model. Specifically, rain attenuation in the Ka band and X band of the SATCOM link for both uplink and downlink scenarios are presented. The weather model for the SATCOM link uses a Markov chain model with an average probability and transition probability for different states of weather, to investigate the impact of dynamic weather on the SATCOM link channel propagation model. Also, a power control method is proposed to achieve the required carrier to noise ratio in a SATCOM scenario using a Bayesian Network in Netica. The Bayesian Network models the space-ground link geometry and transmit power control to adapt to the dynamic weather. Simulations are implemented for the weather states during relatively long and short periods, path loss variations, and transmit power distributions over different scenarios. The simulation results demonstrate the effectiveness of the proposed weather model, Markov chain model, and the power control method for SATCOM.

Satellite systems including the Global Navigation Satellite System (GNSS) and the satellite communications (SATCOM) system provide great convenience and utility to human life including emergency response, wide area efficient communications, and effective transportation. Elements of satellite systems incorporate technologies such as navigation with the global positioning system (GPS), satellite digital video broadcasting, and information transmission with a very small aperture terminal (VSAT), etc. The satellite systems importance is growing in prominence with end users’ requirement for globally high data rate transmissions; the cost reduction of launching satellites; development of smaller sized satellites including cubesat, nanosat, picosat, and femtosat; and integrating internet services with satellite networks. However, with the promising benefits, challenges remain to fully develop secure and robust satellite systems with pervasive computing and communications. In this paper, we investigate both cyber security and radio frequency (RF) interferences mitigation for satellite systems, and demonstrate that they are not isolated. The action space for both cyber security and RF interferences are firstly summarized for satellite systems, based on which the mitigation schemes for both cyber security and RF interferences are given. A multi-layered satellite systems structure is provided with cross-layer design considering multi-path routing and channel coding, to provide great security and diversity gains for secure and robust satellite systems.

This paper develops and evaluates a satellite orbital testbed (SOT) for satellite communications (SATCOM). SOT can emulate the 3D satellite orbit using the omni-wheeled robots and a robotic arm. The 3D motion of satellite is partitioned into the movements in the equatorial plane and the up-down motions in the vertical plane. The former actions are emulated by omni-wheeled robots while the up-down motions are performed by a stepped-motor-controlled-ball along a rod (robotic arm), which is attached to the robot. The emulated satellite positions will go to the measure model, whose results will be used to perform multiple space object tracking. Then the tracking results will go to the maneuver detection and collision alert. The satellite maneuver commands will be translated to robots commands and robotic arm commands. In SATCOM, the effects of jamming depend on the range and angles of the positions of satellite transponder relative to the jamming satellite. We extend the SOT to include USRP transceivers. In the extended SOT, the relative ranges and angles are implemented using omni-wheeled robots and robotic arms.

Satellite Control Networks (SCN) have provided launch control for space lift vehicles; tracking, telemetry and commanding (TTC) for on-orbit satellites; and, test support for space experiments since the 1960s. Currently, SCNs encounter a new challenge: how to maintain the high reliability of services when sharing the spectrum with emerging commercial services. To achieve this goal, the capability of multiple satellites reception is deserved as an update/modernization of SCN in the future. In this paper, we conducts an investigation of multiple access techniques in SCN scenario, e.g., frequency division multiple access (FDMA) and coded division multiple access (CDMA). First, we introduce two upgrade options of SCN based on FDMA and CDMA techniques. Correspondingly, we also provide their performance analysis, especially the system improvement in spectrum efficiency and interference mitigation. Finally, to determine the optimum upgrade option, this work uses CRISP, i.e., Cost, Risk, Installation, Supportability and Performance, as the baseline approach for a comprehensive trade study of these two options. Extensive numerical and simulation results are presented to illustrate the theoretical development.

In this paper we consider a problem of estimating the signal-to-interference-plus-noise ratio (SINR) for satellite transmission system in the presence of jamming signals. Additive white Gaussian noise (AWGN) channels are considered for baseband quadrature phase shift keying (QPSK) data transmission system. Two interference models are proposed with Gaussian or non-Gaussian interference signals in order to investigate the SINR for different satellite transmission jamming scenarios. Both non-data-aided moment-based and data-aided maxi-mum likelihood SINR estimators are derived for the systems. The normalized mean square errors of the SINR estimation algorithms are examined by means of computer simulations. The numerical results show the robust-ness of derived SINR estimators. The development of the SINR estimators are applicable to a large number of applications utilizing satellite communication systems.

This paper investigates the constellation and mapping optimization for amplitude phase shift keying (APSK) modulation, which is deployed in Digital Video Broadcasting Satellite - Second Generation (DVB-S2) and Digital Video Broadcasting - Satellite services to Handhelds (DVB-SH) broadcasting standards due to its merits of power and spectral efficiency together with the robustness against nonlinear distortion. The mapping optimization is performed for 32-APSK according to combined cost functions related to Euclidean distance and mutual information. A Binary switching algorithm and its modified version are used to minimize the cost function and the estimated error between the original and received data. The optimized constellation mapping is tested by combining DVB-S2 standard Low-Density Parity-Check (LDPC) codes in both Bit-Interleaved Coded Modulation (BICM) and BICM with iterative decoding (BICM-ID) systems. The simulated results validate the proposed constellation labeling optimization scheme which yields better performance against conventional 32-APSK constellation defined in DVB-S2 standard.

In this work, we propose a novel beam-forming power allocation method for a satellite communication (SATCOM) multiple-input multiple-output (MIMO) system to mitigate the co-channel interference (CCI) as well as limiting the signal leakage to the adversary users. In SATCOM systems, the beam-forming technique is a conventional way of avoiding interference, controlling the antenna beams, and mitigating undesired signals. We propose to use an advanced beam-forming technique which considers the number of independent channels used and transmitting power deployed to reduce and mitigate the unintentional interference effect. With certain quality of service (QoS) for the SATCOM system, independent channels components will be selected. It is desired to use less and stronger channel components when possible. On the other hand, considering that SATCOM systems often face the problem that adversary receiver detects the signal, a proposed power allocation method can efficiently reduce the received power at the adversary receiver. To reduce the computational burden on the transponder in order to minimize the size, mass, power consumption and delay for the satellite, we apply a hybrid onboard and ground based beam-forming design to distribute the calculation between the transponder and ground terminals. Also the digital channelizer beam-forming (DCB) technique is employed to achieve dynamic spatial control.

Emerging satellite communication (SATCOM) systems are envisioned to incorporate advanced capabilities for dynamically adapting link and network configurations to meet user performance needs. These advanced capabilities require an understanding of the operating environment as well as the potential outcomes of adaptation decisions. A SATCOM situational awareness and decision-making approach is needed that represents the cause and effect linkage of relevant phenomenology and operating conditions on link performance. Similarly, the model must enable a corresponding diagnostic capability that allows SATCOM payload managers to assess likely causes of observed effects. Prior work demonstrated the ability to use a probabilistic reasoning model for a SATCOM situational awareness model. It provided the theoretical basis and demonstrated the ability to realize such a model. This paper presents an analysis of the probabilistic reasoning approach in the context of its ability to be used for diagnostic purposes. A quantitative assessment is presented to demonstrate the impact of uncertainty on estimation accuracy for several key parameters. The paper also discusses how the results could be used by a higher-level reasoning process to evaluate likely causes of performance shortfalls such as atmospheric conditions, pointing errors, and jamming.

The Solar irradiance and Earth Radiation Budget (SERB) mission is an innovative proof-of-concept nano-satellite, with three ambitious scientific objectives. The nano-satellite aims at measuring on the same platform the absolute value of the total solar irradiance (TSI) and its variability, the ultraviolet (UV) solar spectral variability, and the different components of the Earth radiation budget. SERB is a joint project between CNES (Centre National d'Etudes Spatiales), Ecole polytechnique, and LATMOS (Laboratoire Atmospheres, Milieux, Observations Spatiales) scheduled for a launch in 2020–2021. It is a three-unit CubeSat (X-CubeSat II), developed by students from ´Ecole polytechnique. Critical components of instrumental payloads of future large missions (coatings, UV filters, etc.) can acquire the technical maturity by flying in a CubeSat. Nano-satellites also represent an excellent alternative for instrumentation testing, allowing for longer flights than rockets. More-over, specific scientific experiments can be performed by nano-satellites. This paper is intended to present the SERB mission and its scientific objectives.

Outer space has the potential to become the battlefield of the 21st century. If this occurs, the United States will need to invest heavily into research and development regarding space assets, construction approaches, and anti-satellite technologies in order to ensure the requisite level of offensive and deterrent capabilities exist. One challenge that the U.S. faces is the expense of inserting satellites into orbit. With an in-space 3D printer, engineers would not need to incur the design and construction costs for developing a satellite that can survive the launch into orbit. Instead, they could just create the best design for their application and the in-space 3D printer could print and deploy it in orbit. This paper considers the foregoing and other uses for a 3D printer in space that advance national security.

This paper presents a space mission enablement and cost reduction technology: in-space 3D printing. Using in-space 3D printing, spacecraft can be lighter, require less launch volume and be designed solely for orbital operations. The proposed technology, which supports various thermoplastics and prospectively metals, is presented in detail. Key subsystems such as the energy collection system, the melting unit, and the printing unit are explained.

There is a rapidly growing need for position, navigation, and timing (PNT) capability that remains effective when GPS is degraded or denied. Naturally occurring sky polarization was used as long ago as the Vikings for navigation purposes. With current polarimetric sensors, the additional polarization information measured by these sensors can be used to increase the accuracy and the availability of this technique. The Sky Polarization Azimuth Sensing System (SkyPASS) sensor measures this naturally occurring sky polarization to give absolute heading information to less than 0.1° and offers significant performance enhancement over digital compasses and sun sensors. SkyPASS has been under development for some time for terrestrial applications, but use above the atmosphere may be possible and the performance specifications and SWAP are attractive for use as an additional pose sensor on a satellite. In this paper, we will describe the phenomenology, the sensor performance, and the latest test results of terrestrial SkyPASS; we will also discuss the potential for use above the atmosphere and the expected benefits and limitations.

Ionizing radiation poses a significant challenge for Earth-based defense applications as well as human and/or robotic space missions. Practical sensors based on luminescence will depend heavily upon research investigating the resistance of these materials to ionizing radiation and the ability to anneal or self-heal from damage caused by such radiation. In 1951, Birks and Black showed experimentally that the luminescent efficiency of anthracene bombarded by alphas varies with total fluence (N) as (I/I₀) = 1/(1 + AN), where I is the luminescence yield, I₀ is the initial yield, and A is a constant. The half brightness (N_1/2) is defined as the fluence that reduce the emission light yield to half and is equal to is the inverse of A. Broser and Kallmann developed a similar relationship to the Birks and Black equation for inorganic phosphors irradiated using alpha particles. From 1990 to the present, we found that the Birks and Black relation describes the reduction in light emission yield for every tested luminescent material except lead phosphate glass due to proton irradiation. These results indicate that radiation produced quenching centers compete with emission for absorbed energy. The purpose of this paper is to present results from research completed in this area over the last few years. Particular emphasis will be placed on recent measurements made on new materials such as europium tetrakis dibenzoylmethide triethylammonium (EuD₄TEA). Results have shown that EuD₄TEA with its relatively small N_1/2 might be a good candidate for use as a personal proton fluence sensor.

A device capable of creating tethers for use with spacecraft that are made from a diverse material palette could serve many functions. These functions include supporting applications such as data transfer, power generation, and resource collection. Applications that are currently being considered include use in a system for orientation, data transfer, and power delivery and use as part of a free-moving camera system which would be used in proximity to a spacecraft for capturing images and video for promotional and preforming diagnostic and “self-check” operations. Materials that have been considered for use in such a tethering device have different physical attributes in order to facilitate supporting the widest possible degree of applications for use in scientific, remote sensing, power generation, and electromagnetic applications methods for the parent spacecraft. Physical properties that have been considered include: rigidity, conductivity, heat dissipation, and opacity. The proposed dynamic tethering system would be driven by 3D printing technologies. This prospective application of 3D printing remains relatively unexplored. This provides great opportunities for knowledge expansion and the development of dynamic tethers for use capturing video footage and pictures, and for other scientific endeavors.

The National Imagery Interpretability Rating Scale (NIIRS) is a subjective quantification of static image widely adopted by the Geographic Information System (GIS) community. Efforts have been made to relate NIIRS image quality to sensor parameters using the general image quality equations (GIQE), which make it possible to automatically predict the NIIRS rating of an image through automated image analysis. In this paper, we present an automated procedure to extract line edge profile based on which the NIIRS rating of a given image can be estimated through the GIQEs if the ground sampling distance (GSD) is known. Steps involved include straight edge detection, edge stripes determination, and edge intensity determination, among others. Next, we show how to employ GIQEs to estimate NIIRS degradation without knowing the ground truth GSD and investigate the effects of image compression on the degradation of an image’s NIIRS rating. Specifically, we consider JPEG and JPEG2000 image compression standards. The extensive experimental results demonstrate the effect of image compression on the ground sampling distance and relative edge response, which are the major factors effecting NIIRS rating.

In this paper, we present an approach to remote control of a mobile robot via a Google Glass with the multi-function and compact size. This wearable device provides a new human-machine interface (HMI) to control a robot without need for a regular computer monitor because the Google Glass micro projector is able to display live videos around robot environments. In doing it, we first develop a protocol to establish WI-FI connection between Google Glass and a robot and then implement five types of robot behaviors: Moving Forward, Turning Left, Turning Right, Taking Pause, and Moving Backward, which are controlled by sliding and clicking the touchpad located on the right side of the temple. In order to demonstrate the effectiveness of the proposed Google Glass-based remote control system, we navigate a virtual Surveyor robot to pass a maze. Experimental results demonstrate that the proposed control system achieves the desired performance.