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Discusses the application of space-time adaptive processing (STAP) and related adaptive array techniques in improving sensor performance by signal diversity. History of adaptive array research; Factors considered in STAP analysis.

As you may know, the M Barry Carlton Award is bestowed on the authors of the best paper published in the IEEE Transactions of Aerospace and Electronic Systems (T-AES) for a given calendar year. The winners for the 2011 Award were announced in the February issue earlier this year. It is now my privilege to announce that the 2012 M Barry Carlton award winners are Kevin (Jim) Sangston, Fulvio Gini, and Maria (Sabrina) Greco for their paper entitled, "Coherent Radar Target Detection in Heavy-Tailed Compound-Gaussian Clutter." [ABSTRACT FROM AUTHOR]

In this day and age, we have an incredible wealth of knowledge available at our fingertips. This is also increasing the rate of new discoveries. The amount of content in our knowledge repositories such as in IEEE Xplore is growing exponentially. While the easy access to knowledge is helping to drive this growth, there are other less wondrous forces that are at play. In fact, the amount of knowledge within Xplore might be growing far less than the content, and IEEE is very concerned that many duplicative papers are in the archives. This may have a detrimental effect on the enthusiasm for subscriptions that IEEE can expect from libraries, and it is libraries that provide the critical financial support of IEEE?s scholarly operations. Furthermore, duplicative content means that the precious time of valuable volunteer editors and reviewers is being wasted. [ABSTRACT FROM PUBLISHER]

Inertial navigation computation is to acquire the attitude, velocity, and position information of a moving body by integrating inertial measurements from gyroscopes and accelerometers. Over half a century has witnessed great efforts in coping with the motion noncommutativity errors to accurately compute the navigation information as far as possible, so as not to compromise the quality measurements of inertial sensors. Highly dynamic applications and the forthcoming cold-atom precision inertial navigation systems demand for even more accurate inertial navigation computation. The paper gives birth to an inertial navigation algorithm to fulfill that demand, named the iNavFIter, which is based on a brand-new framework of functional iterative integration and Chebyshev polynomials. Remarkably, the proposed iNavFIter reduces the noncommutativity errors to almost machine precision, namely, the coning/sculling/scrolling errors that have perplexed the navigation community for long. Numerical results are provided to demonstrate its accuracy superiority over the state-of-the-art inertial navigation algorithms at affordable computation cost. [ABSTRACT FROM AUTHOR]

In a network of cooperating unmanned aerial vehicles (UAVs), individual UAVs usually need to localize themselves in a shared and generally global frame. This paper studies the localization problem for a group of UAVs navigating in three-dimensional space with limited shared information, viz., noisy distance measurements are the only type of interagent sensing that is available, and only one UAV knows its global coordinates, the others being GPS denied. Initially, for a two-agent problem, but easily generalized to some multiagent problems, this paper first establishes constraints on the minimum number of distance measurements required to achieve the localization. This paper then proposes a composite algorithm based on semidefinite programming (SDP) in a first step, followed by maximum likelihood estimation using gradient descent on a manifold initialized by the SDP calculation. The efficacy of the algorithm is verified with experimental noisy flight data. [ABSTRACT FROM AUTHOR]

Measuring the vibrating states of an artificial structure is an important approach to monitor the stability of the structure. However, the existing radar vibration measurement methods do not have enough azimuth resolution for measuring the vibrations in a relatively large scene, which contains multiple buildings or a large building. For such application scene, this paper proposes a vibration measurement method based on multiple-input multiple-output imaging radar system, which can achieve high azimuth resolution. Features of the proposed method are threefold: first of all, by utilizing the ability of quickly acquiring imaging data, the proposed method can achieve vibration measurement for the entire area simultaneously; second, in order to detect the positions of vibrating objects and decrease the time of vibration parameter estimation part, this paper proposes vibration similarity index to quantify the similarity between the detected signal and ideal vibration signal; at last, due to the limitations of the hardware performance, this paper adopts multiple signal classification least-squares estimation method to estimate the vibrating frequency and amplitude. To evaluate the performance of the proposed method, ideal point target simulation and vibrating calibrator experiment have been conducted, and the results show that the positions and the vibrating parameters of the vibrating objects fit well with the reference values. In addition, car experiment and bridge experiment have been carried out to verify the ability of the proposed method to measure the vibration of real artificial structures, which cannot be seen as point targets. [ABSTRACT FROM AUTHOR]

This paper deals with the impulsive formation control of spacecraft in the presence of constraints on the position vector and time. Determining a set of path constraints can increase the safety and reliability in an impulsive relative motion of spacecraft. Specially, the feasibility problem of the position norm constraints is considered in this paper. Under assumptions, it is proved that if a position vector be reachable, then the reach time and the corresponding time of impulses are unique. The trajectory boundedness of the spacecraft between adjacent impulses are analyzed using the Gerschgorin and the Rayleigh–Ritz theorems as well as a finite form of the Jensen's inequality. Some boundaries are introduced regarding the Jordan–Brouwer separation theorem which are useful in checking the satisfaction of a constraint. Two numerical examples (approximate circular formation keeping and collision-free maneuver) are solved in order to show the applications and visualize the results. [ABSTRACT FROM AUTHOR]

This note revisits the theoretical foundation of the Daum–Huang particle filter concepts for solving Bayesian updating problems. We reexamine the defining necessary and sufficient condition, in the form of an operator equation, for a flow to generate a particular homotopy between the a priori and the a posteriori probability density functions. We show that two well-known flows indeed satisfy this sufficient condition in the linear-Gaussian case, restating some of the significant results in a recent series of papers coauthored by Fred Daum with our alternative proof, which we hope will provide a useful perspective for future flow-based filter developments. [ABSTRACT FROM AUTHOR]

Multiple cell upsets (MCU) is an issue that has to be dealt with when designing electronics for working in a radiated environment. Furthermore, the constant evolution of ICs integration density causes an increment in the MCUs span. These issues are typical in aviation applications, where, additionally, fault-tolerant (FT) performance is required. FT systems are typically based on a redundancy concept for storing and retrieving healthy information, for example, with a triple modular redundancy (TMR) scheme. The main issue with redundancy is design oversizing. On the other hand, reconfiguration-based techniques allow error scrubbing with a limited overhead. The main drawback here is overhead vulnerability to radiation, which is invalid for FT requirements. This paper proposes a new hybrid architecture that takes advantage of the optimized performance of reconfiguration-based techniques supported on extremely compressed redundant information nonvulnerable to radiation, referred to in this paper as hardwired seed bits (HSB). It also includes different known techniques, such as interleaving, error detection and correction (EDAC) algorithms, etc., for optimizing the final architecture as much as possible. As a result, the proposed approach meets FT requirements thanks to nonvulnerable tiny redundant information combined with an optimized performance through EDAC-based implementation. [ABSTRACT FROM AUTHOR]

This paper proposes a low budget solution to detect and possibly track space debris and satellites in Low Earth Orbit. The concept consists of a space-borne radar installed on a cubeSat flying at low altitude and detecting the occultations of radio signals coming from existing satellites flying at higher altitudes. The paper investigates the feasibility and performance of such a passive bistatic radar system. Key performance metrics considered in this paper are: the minimum size of detectable objects, considering visibility and frequency constraints on existing radio sources, the receiver size, and the compatibility with current cubeSat's technology. Different illuminator types and receiver altitudes are considered under the assumption that all illuminators and receivers are on circular orbits. [ABSTRACT FROM AUTHOR]

This article deals with error models for a trident quaternion framework proposed in the companion paper (Part I) and further uses them to investigate the odometer-aided static/in-motion inertial navigation attitude alignment for land vehicles. By linearizing the trident quaternion kinematic equation, the left- and right-trident-quaternion error models are obtained, which are found to be equivalent to those derived from profound group affine. The two error models are used to design their corresponding extended Kalman filters (EKFs), namely, the left-quaternion EKF (LQEKF) and the right-quaternion EKF (RQEKF). Simulations and field tests are conducted to evaluate their actual performances. Owing to the high estimation consistency, the LQEKF and the RQEKF converge much faster in the static alignment than the traditional error-model-based EKF, even under arbitrary large heading initialization. For the in-motion alignment, the LQEKF and the RQEKF possess much larger convergence region than the traditional EKF does, although they still require the aid of attitude initialization so as to avoid large initial attitude errors. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of a divisible nonlinear load distribution on homogeneous complete b-ary tree networks. Classic models of nonlinear computational loads omit several steps in processing the load and yield only an approximate distribution for fractional loads. This paper considers a new model of nonlinear computational loads that includes all load processing steps and yields a practical solution to distribute fractional loads. Two algorithms to distribute a divisible nonlinear load on homogeneous complete b-ary tree networks are proposed. Closed-form expressions for the parallel processing time and speed-up for complete b-ary trees are also derived. This paper demonstrates that the asymptotic speed-up of the proposed algorithms is the number of processors in a multicomputer system. The proposed algorithms improved the classic algorithm in terms of speed-up. [ABSTRACT FROM AUTHOR]

This paper deals with the practical aspects of development of multisatellite communication system. Specifically, the problem of data detection in multisatellite communication system is discussed in this paper. All satellites want to communicate to a particular earth station (ES). A novel interference cancellation method is used to obtain the data of different satellites at the ES. Based on the standard moment generating function approach, the proposed system is evaluated by analyzing the symbol error rate, diversity order, and average capacity. It is shown through simulation and analysis that the number of antennas at the ES should be sufficiently large as compared to the number of satellites in order to achieve good performance and improved diversity gain and average capacity. It is also shown that the diversity order of the considered system does not depend upon the shadowing environment. By placing more antennas at the ES, the effect of channel (shadowing) can be compensated. [ABSTRACT FROM AUTHOR]

This paper proposes an optimal arrangement framework of ballistic missile defense systems, such as a launcher and radar to maximize the survivability of protected assets. In order to solve the optimization problem through a probabilistic approach, we derive a single shot kill probability (SSKP) model based on engagement geometries, trajectory characteristic of an interceptor and a ballistic missile, and error models embedded in both an interceptor and radar. This SSKP model is useful to predict a performance of defense systems in early design phase or to draw requirements of subsystems. After an SSKP model is derived, we present a framework to calculate the survivability of protected assets. In the framework, we establish a concept of survivability distributions of the protected assets, which vary with the arrangement of defense systems. By using the survivability distributions for given protected assets, the optimal location of a launcher and radar can be derived. The potential significance of the proposed framework is that it can be directly applicable in real defense systems by just substituting SSKP models derived in this paper with more sophisticatedly derived SSKP distributions. Finally, the optimal arrangements are derived by the proposed framework and the effectiveness of the results is evaluated through various case studies. [ABSTRACT FROM AUTHOR]

The quad-phase codes of a given length may be organized into equivalence classes relative to a set of operations preserving autocorrelation peak sidelobe level (PSL). Knowledge about these equivalence classes can be exploited for faster searches or for efficient listing of low- $\rm PSL$ codes. This paper is part of an effort to enumerate autocorrelation $\rm PSL$ equivalence classes for quad-phase codes of any length. An earlier paper achieved a formula for the number of $\rm PSL$ equivalence classes for even lengths $N \geq 2$ , as well as a simple algorithm for generating equivalence class representatives. This paper completes the enumeration task by extending the same formula to the odd lengths $N \geq 3$. The results make use of work by Yurramendi in enumerating equivalence classes for binary rectangular grids relative to horizontal reflection and vertical reflection. In addition, a method is described for generating a minimal set of $\rm PSL$ equivalence class representatives covering the space of quad-phase codes of any odd length $N > 3$. [ABSTRACT FROM AUTHOR]

This paper proposes an autopilot design for an interceptor with thrust vector control that operates in the endo- and exoatmospheric regions. The main objective of the proposed autopilot design is to ensure control performance in both atmospheric regions, without changing the control mechanism. In this paper, the characteristics of the aerodynamic forces in both atmospheric regions are first investigated to examine the issue of the conventional control mechanism at various altitudes. And then, a control mechanism, which can be applied to both atmospheric regions, is determined based on the analysis results. An autopilot design is then followed by utilizing the control mechanism and the feedback linearization control method. Accordingly, the proposed autopilot does not rely on changing the control mechanism depending on flight condition unlike the conventional approach, however it can adjust the control gains automatically according to the changes in flight operating conditions. In this paper, the robustness of the proposed autopilot is investigated through the tracking error analysis and the relative stability analysis in the presence of model uncertainties. The physical meaning of the proposed autopilot is also presented by comparing to the well-known three-loop control structure. Finally, numerical simulations are performed to show the performance of the proposed method. [ABSTRACT FROM AUTHOR]

In the fractional frequency reuse (FFR) system, the bandwidth is partitioned into orthogonal subbands such that users in the cell-center region use the subbands of a frequency reuse factor (FR factor) equal to 1, whereas users in the cell-edge region exploit the subbands of an FR factor larger than 1. The distance threshold, which is used to distinguish the cell-edge region from the cell-center region, is an important factor in FFR system performance. In this paper, we study the optimal distance threshold to maximize system throughput in the downlink cellular networks, including aerial base stations. Subject to the constraint that a given target outage probability is satisfied, the optimal distance threshold is analyzed as a function of the cell size. It is proven that when the sizes of all cells in the network are scaled at the same rate, the optimal distance threshold normalized by the cell size is nondecreasing in the cell size. The analytical results in this paper provide a system design guideline for initial planning of FFR cellular networks of different sizes, including macro, pico, and femto systems. In particular, for size-scalable aerial networks comprising base stations in the sky, such as balloons or unmanned aerial vehicles, our analysis offers insight into the design of the distance threshold with regard to the cell size. [ABSTRACT FROM AUTHOR]

Interplanetary networks are affected by long propagation delays, intermittent connectivity, possible packet losses due to residual errors, and other impairments. To cope with these challenges, the delay-/disruption-tolerant networking (DTN) architecture utilizes the Licklider transmission protocol (LTP) as convergence layer on space links. The LTP reliable service (red) relies on Automatic Repeat reQuest, but very long propagation delays make packet layer forward error correcting (PL-FEC) codes very appealing to protect LTP segments from losses. The key advantage of FEC is that LTP retransmissions would be limited to the unlikely case of decoding failures. To this end, a new FEC-based protocol, to be inserted immediately below LTP, the erasure coding link service adapter (ECLSA), is presented here. ECLSA is completely transparent to LTP, relies on two alternative external libraries for coding/decoding, LibecDLR and OpenFEC, both using low density parity check codes and it is fully integrated with the ION DTN software package of NASA-JPL. This paper aims to provide a solid description of ECLSA, including features functional in a real deployment (such as the dynamic selection of codes). Performance is evaluated at the end of the paper, with nearly ideal results. ECLSA is released as free software and is already included in the “contrib” section of ION. [ABSTRACT FROM AUTHOR]

This paper deals with measurement extraction, from an optical sensor's Focal Plane Array (FPA), of a streaking target. We use a model that assumes pixels are separated by dead zones and model the streaking target's point spread function (PSF) as a Gaussian PSF that moves during the optical sensor's integration time. We make an assumption that the target has a constant velocity over the sampling interval and parametrize its motion with a starting and ending position. The noise model for a single pixel has variance proportional to its area, consistent with a Poisson model of the number of nontarget originated photons. We develop a maximum likelihood (ML) method of estimating the target motion parameter vector based on the set of pixel measurements from the optical sensor. This paper then derives the Cramer–Rao lower bound (CRLB) on the estimation error of the target motion parameter. We then present a matched filter (MF) based definition of the signal-to-noise ratio (SNR) to use as a basis for comparison of Monte Carlo simulation based location estimates to the calculated CRLB. It is shown that the ML estimator for the starting and ending positions of a streak in the FPA is efficient for MFSNR $\geq 12$  dB. We then provide a test statistic for target detection and propose approximate distributions to set the detection threshold for specific detection ($P_D$) and false alarm probabilities ($P_{\text{FA}}$), which are then verified via simulations. This paper's major contributions are the proposal of an ML/MF method for measurement extraction of streaking targets, confirmation that this method achieves the best accuracy possible for realistic FPA sensors, i.e., it attains the CRLB, the introduction of a statistically supported definition of SNR for these measurements, and an evaluation of the target measurement detection performance. Furthermore, this paper shows that, given our MFSNR definition, the streak length and direction of motion in the FPA have a negligible effect on performance compared to the SNR where we show that with a 4-dB change, the detection performance increases dramatically. [ABSTRACT FROM AUTHOR]

This paper addresses the performance characterization of a direction of arrival (DoA) estimator in the low signal-to-noise-ratio (SNR) region. The case of a sensor array simultaneously collecting signals emitted at multiple carrier frequencies by a single source is considered. A maximum likelihood (ML) approach is used as a reference method for DoA estimation and its accuracy is characterized in terms of mean square error (MSE). It is well known that for SNR values included in the so-called threshold region, the DoA estimation accuracy decreases rapidly, due to the presence of outliers. This effect can be possibly mitigated when multiple frequency channels are jointly exploited. However, the capability to predict this performance degradation is fundamental either for assessing the robustness of an existing sensor or for supporting its design. Therefore, the scope of this paper is to introduce appropriate approximations to the MSE of a multifrequency ML DoA estimator in order to provide a reliable characterization of its performance in the threshold region. Two models for the source signals are considered and separately discussed, namely the deterministic (or conditional) and stochastic (or unconditional). An extensive simulated analysis is reported to prove the tightness of the approximations and to characterize the benefits steming from the exploitation of signals emitted at multiple carriers. [ABSTRACT FROM AUTHOR]

This paper presents a method for spacecraft to achieve the task of fast maneuvering and fast stabilization. To realize this task, a new type of vibration isolation platform whose actuators are based on magnetic suspension techniques and an attitude controller to suit the spacecraft with this new vibration isolation platform are presented. High-frequency vibrations would reduce the stability of the attitude control, and low-frequency vibrations would reduce the maneuvering time of the attitude control. The vibration isolation platform presented in this paper is assembled between the spacecraft bus and the attitude control actuators and acts to reduce the high-frequency vibrations. The vibration isolation platform, which consists of the vibration isolation strut with magnetic suspension, has better performance in the region of high frequency according to the frequency-domain analysis. An appropriate controller for the vibration isolation strut is designed based on the frequency-domain analysis. Then, the attitude controller of the spacecraft bus is designed using the finite-time control theory to reduce the low-frequency vibrations, thus reducing the maneuvering time. Finally, the numerical simulations show that the vibration isolation platform and the attitude controller do work and cooperate well. [ABSTRACT FROM AUTHOR]

This paper presents an efficient method for estimating the probability of conflict between air traffic within a block of airspace. Autonomous sense-and-avoid is an essential safety feature to enable unmanned air systems to operate alongside other (manned or unmanned) air traffic. The ability to estimate the probability of conflict between traffic is an essential part of sense-and-avoid. Such probabilities are typically very low. Evaluating low probabilities using naive direct Monte Carlo generates a significant computational load. This paper applies a technique called subset simulation. The small failure probabilities are computed as a product of larger conditional failure probabilities, reducing the computational load while improving the accuracy of the probability estimates. The reduction in the number of samples required can be one or more orders of magnitude. The utility of the approach is demonstrated by modeling a series of conflicting and potentially conflicting scenarios based on the standard Rules of the Air. [ABSTRACT FROM AUTHOR]

Automatic target recognition (ATR) is an important part for many computer vision applications. Despite the extensive research which has been carried out in this area for many years, there is no ATR system which performs well on all applications. Recently, different object recognition frameworks have been proposed which yield a high performance in baseline databases. However, our experiments showed that they can fail in real-world scenarios, when dealing with a limited number of data samples. In this paper, we propose a new ATR system, based on deep convolutional neural network (DCNN), to detect the targets in forward looking infrared (FLIR) scenes and recognize their classes. In our proposed ATR framework, a fully convolutional network is trained to map the input FLIR imagery data to a fixed stride correspondingly-sized target score map. The potential targets are identified by applying a threshold on the target score map. Finally, the corresponding regions centered at these target points are fed to a DCNN to classify them into different target types while at the same time rejecting the false alarms. The proposed architecture achieves a significantly better performance in comparison with that of the state-of-the-art methods on two large FLIR image databases. [ABSTRACT FROM AUTHOR]

The coexistence between radar and communications systems has received considerable attention from the research community in the past years. In this paper, a radar waveform design method for target parameter estimation is proposed. Target time delay parameter is used as an example. The case where the two systems are not colocated is considered. Radar waveform optimization is performed using statistical criteria associated with estimation performance, namely Fisher Information (FI) and Cramér–Rao Bound (CRB). Expressions for FI and CRB are analytically derived. Optimization of waveforms is performed by imposing constraints on the total transmitted radar power, constraints on the interference caused to the communications system, as well as constraints on the subcarrier power ratio (SPR) of the radar waveform. The frequency-domain SPR is different than the peak-to-average power ratio, which is computed in time domain. It is shown, using simulation results, that the proposed optimization strategies outperform other strategies in terms of estimation error. It is also shown that the SPR constraint reduces the delay domain ambiguities. [ABSTRACT FROM AUTHOR]

The development of a multiple model-based identification algorithm is addressed in this paper for nonlinear modeling of a conventional aircraft in the entire flight envelope. The dynamic model of an aircraft varies significantly depending on changes in the flight condition of the air vehicle including the altitude and the equivalent air speed. Therefore, the conventional identification approaches for generating a single nonlinear model with time-invariant parameters cannot be used in the entire flight envelope of an aircraft. Accordingly, a multiple model-based approach using nonlinear autoregressive exogenous neural networks is introduced in this paper as a powerful tool in identifying complex nonlinear dynamic systems. Different methods of validity function determination are introduced in order to aggregate the separate local models into a single model. The obtained results show that the proposed approach using the extreme learning machine-based validity function determination method has a significant capability to predict the aircraft outputs in various flight conditions. Further, the proposed identification scheme can be used effectively as a precise multistep ahead predictor of nonlinear multivariable systems outputs. [ABSTRACT FROM AUTHOR]

Accurate location information is essential for mobile systems such as wireless sensor networks. A location-aware sensor network generally includes two types of nodes: Sensors whose locations to be determined and anchors whose locations are known a priori. For range-based cooperative positioning, sensors’ locations are deduced from anchor-to-sensor and sensor-to-sensor range measurements. Positioning accuracy depends on the network parameters such as network connectivity and size. This paper provides a generalized theory that quantitatively characterizes such a relation between network parameters and positioning accuracy. We use the average degree as a connectivity metric and use geometric dilution of precision (DOP) to quantify positioning accuracy. Under the assumption that nodes are randomly deployed, we prove a novel lower bound on expectation of average geometric DOP (LB-E-AGDOP) and derives a closed-form formula that relates LB-E-AGDOP to only three parameters: Average anchor degree, average sensor degree, and number of sensor nodes. The formula shows that positioning accuracy is approximately inversely proportional to the average degree, and a higher ratio of average anchor degree to average sensor degree yields better positioning accuracy. Furthermore, the paper shows a strong connection between LB-E-AGDOP and the best achievable accuracy. Finally, we demonstrate the theory via numerical simulations with three different random graph models. [ABSTRACT FROM PUBLISHER]

This paper deals with a symbiotic radar, defined as a passive radar that is an integral part of a communication network. The symbiotic radar is integrated with an IEEE 802.22 Wireless Regional Area Network and linked with the base station. It can work as a purely passive radar or, and this is the novelty in the system, can use the base station to suggest the best customer premise equipment that should be scheduled for transmission to improve tracking performance. This paper defines a cognitive passive tracking algorithm that exploits the feedback information contained in the target state prediction to improve the performance while preserving the communication capabilities of the complete network. [ABSTRACT FROM PUBLISHER]

This paper addresses the problem of reliability and makespan optimization of hardware task graphs in reconfigurable platforms by applying fault tolerance (FT) techniques to the running tasks based on the exploration of the Pareto set of solutions. In the presented solution, in contrast to the existing approaches in the literature, task graph scheduling, tasks parallelism, reconfiguration delay, and FT requirements are taken into account altogether. This paper first presents a model for hardware task graphs, task prefetch and scheduling, reconfigurable computer, and a fault model for reliability. Then, a mathematical model of an integer nonlinear multi-objective optimization problem is presented for improving the FT of hardware task graphs, scheduled in partially reconfigurable platforms. Experimental results show the positive impacts of choosing the FT techniques selected by the proposed solution, which is named Pareto-based. Thus, in comparison to nonfault-tolerant designs or other state-of-the-art FT approaches, without increasing makespan, about 850% mean time to failure (MTTF) improvement is achieved and, without degrading reliability, makespan is improved by 25%. In addition, experiments in fault-varying environments have demonstrated that the presented approach outperforms the existing state-of-the-art adaptive FT techniques in terms of both MTTF and makespan. [ABSTRACT FROM PUBLISHER]

Statistical parameters of the beat signal of the frequency-modulated continuous-wave (FMCW) radar altimeter in case of scattering from cylindrical rough surface are determined in the Kirchhoff approximation. A concept of the double dimensionality of the beat signal is formulated in this paper. Results of this paper can be used to construct a simple simulation model to assess signal processing algorithms implemented in an FMCW radar altimeter. [ABSTRACT FROM AUTHOR]

Using low-frequency (UHF to L-band) ultrawideband synthetic aperture radar (SAR) technology for detecting buried and obscured targets, e.g., bomb or mine, has been successfully demonstrated recently. Despite promising recent progress, a significant open challenge is to distinguish obscured targets from other (natural and manmade) clutter sources in the scene. The problem becomes exacerbated in the presence of noisy responses from rough ground surfaces. In this paper, we present three novel sparsity-driven techniques, which not only exploit the subtle features of raw captured data, but also take advantage of the polarization diversity and the aspect angle dependence information from multichannel SAR data. First, the traditional sparse representation-based classification is generalized to exploit shared information of classes and various sparsity structures of tensor coefficients for multichannel data. Corresponding tensor dictionary learning models are consequently proposed to enhance classification accuracy. Finally, a new tensor sparsity model is proposed to model responses from multiple consecutive looks of objects, which is a unique characteristic of the data set we consider. Extensive experimental results on a high-fidelity electromagnetic simulated data set and radar data collected from the U.S. Army Research Laboratory side-looking SAR demonstrate the advantages of proposed tensor sparsity models. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of distributed detection in the case where, under the signal-present hypothesis, the signal-to-noise ratio (SNR) is unknown and/or observations are correlated. We assume that each local detector makes a (binary) decision while meeting a local false alarm constraint; it then transmits its decision to a fusion center. The unknown SNR at each local detector induces an unknown probability of detection and, hence, the optimal detector at the fusion center does not exist. We begin with the case most often considered in the literature: independent observations. In this case, we derive the asymptotically optimal separating function estimation test (AOSFET) and the generalized likelihood ratio test (GLRT). Moreover, we propose a method to set the local false alarm rates to achieve the maximum probability of detection at the fusion center (while meeting a constraint on the global probability of false alarm). The second part of this paper considers the case of correlated observations. We show that the AOSFET for this problem does not exist. As alternatives, we propose three suboptimal SFETs: based on an approximation to the AOSFET, the Kullback–Leibler divergence, and the Euclidean distance of the estimated probability mass function (pmf) of the observations under each hypotheses. Finally, we propose two methods to improve the performance of the estimation of the pmfs using a library of training labeled data based on the maximum likelihood estimation and expected maximization methods. [ABSTRACT FROM AUTHOR]

Provisioning of Internet of Things/machine-to-machine (M2M) services over satellite has been experiencing a continuous growth in the last few years, which is expected to further increase in the near future so as to meet the demands of users and enterprises. The design of a suitable network architecture is, hence, of paramount importance to properly take into account the requirements imposed by the technology available nowadays and to properly consider the interaction of the so-defined physical layer with transport and application layers. In this light, this paper analyzes the use case of TCP-based M2M services operating over DVB-RCS2 satellite links, where a contention resolution diversity slotted ALOHA access scheme is applied. The main goal of this paper is to provide a thorough understanding of the interactions of TCP and random access schemes, recognized as key elements to enable efficient M2M services over satellite. In this regard, this paper also develops a novel TCP throughput model, which has been validated through extensive simulation campaigns, proving the value of the proposed theoretical framework and its applicability to study the performance of M2M services in more general satellite scenarios. [ABSTRACT FROM AUTHOR]

Attitude computation is of vital importance for a variety of applications. Based on the functional iteration of the Rodrigues vector integration equation, the RodFIter method can be advantageously applied to analytically reconstruct the attitude from discrete gyroscope measurements over the time interval of interest. It is promising to produce ultra-accurate attitude reconstruction. However, the RodFIter method imposes a high computational load and does not lend itself to an onboard implementation. In this paper, a fast approach to significantly reduce RodFIter's computation complexity is presented while maintaining almost the same accuracy of attitude reconstruction. It reformulates the Rodrigues vector iterative integration in terms of the Chebyshev polynomial iteration. Due to the excellent property of Chebyshev polynomials, the fast RodFIter is achieved by means of appropriate truncation of Chebyshev polynomials, with provably guaranteed convergence. Moreover, simulation results validate the speed and accuracy of the proposed method. [ABSTRACT FROM AUTHOR]

This paper presents the design, implementation, and evaluation of four filters for the estimation of angle of attack (AOA) and angle of sideslip (AOS) of small unmanned aerial vehicles (UAVs). Specifically, two novel filters (a complementary filter and an extended Kalman filter) are proposed and evaluated without using direct flow angle and Global Positioning System measurements; two existing AOA/AOS filters are also implemented and evaluated. All filters are designed with minimal inputs and states to ensure the ease of implementation, simplicity of tuning, and computation efficiency. Both simulation and UAV flight test results show the performance of the proposed filters. Especially, flight test results from two different UAVs (a T-tail UAV and a flying wing UAV) show that the root mean square errors of estimated inertial AOA and AOS are less than 1.5 $^\circ$ under nominal flight conditions and around 2 $^\circ$ under aggressive maneuvers compared with direct flow angle measurements. [ABSTRACT FROM AUTHOR]

Pose estimation is vital for space robot to capture satellite. Dual poses including center position and normal direction can be obtained from a single perspective view of a radius-known circle such as docking ring of the satellite. To solve the duality and recover the roll angle, this paper presents here a new method called perspective circle and line (PCL), which is based on the perspective view of a single circle and line. First of all, the dual center positions and normal directions are recovered with the circle and the image. Then, the line is utilized to recover the roll angle of the circle analytically. By reprojecting a random point on the line to the image and verifying whether the projection lies on the image line, the false pose of the object is identified. Simulation and physical experiments show that the position and orientation of the circle can be recovered. But in practice they are affected by the accuracy of camera calibration and feature extraction. As a whole, PCL is robust to noise in pose estimation, especially in recovering the orientation. [ABSTRACT FROM AUTHOR]

Spectrum awareness techniques have been proposed as a promising solution to improve the utilization of available spectrum bands. However, few works have discussed the feasibility of spectrum awareness techniques in satellite systems. In the scenario of spectrum coexistence between geostationary (GEO) and nongeostationary (NGEO) satellite systems, this paper investigates the issue of blind spot where the spectrum awareness techniques may fail to identify the spectrum holes. Both the uplink and downlink transmissions are analyzed and three key parameters, i.e., altitude of NGEO satellite and antenna diameters of NGEO and GEO earth stations, are considered. Simulation results show that in the uplink, when the NGEO satellite approaches to the GEO satellite with a certain heights, there exists the situation of blind spot. In addition, this paper also provides a specific method to eliminate or reduce the range of blind spot. [ABSTRACT FROM AUTHOR]

Rigid motion computation or estimation is a cornerstone in numerous fields. Attitude computation can be achieved by integrating the angular velocity measured by gyroscopes, the accuracy of which is crucially important for the dead-reckoning inertial navigation. The state-of-the-art attitude algorithms have unexceptionally relied on the simplified differential equation of the rotation vector to obtain the attitude. This paper proposes a functional iteration technique with the Rodrigues vector (named the RodFIter method) to analytically reconstruct the attitude from gyroscope measurements. The RodFIter method is provably exact in reconstructing the incremental attitude as long as the angular velocity is exact. Notably, the Rodrigues vector is analytically obtained and can be used to update the attitude over the considered time interval. The proposed method gives birth to an ultimate attitude algorithm scheme that can be naturally extended to the general rigid motion computation. It is extensively evaluated under the attitude coning motion and compares favorably in accuracy with the mainstream attitude algorithms. This paper is believed having eliminated the long-standing theoretical barrier in exact motion integration from inertial measurements. [ABSTRACT FROM AUTHOR]

This paper introduces a filter for tracking a ballistic missile during its boost phase. This filter includes a new switching algorithm and a modified interacting multiple model unscented filter (IMMUF), where the Markov transition matrix is time variable. Position, velocity, and all unknown parameters of a medium-range ballistic missile model are reconstructed. Simulations demonstrate that the new filter is able to consistently estimate a missile's trajectory and all unknown parameters and to outperform the previous forms of the IMMUF. [ABSTRACT FROM AUTHOR]

To ensure successful future planetary landing mission, the lander must be capable of detecting and assessing terrain hazard in the nominal landing zone. This paper presents an innovative method of planetary terrain hazard detection. The concept of feature density is introduced into the process of terrain hazard detection. Moreover, the statistical information of the terrain feature density is utilized to represent the terrain hazard level. Opposed to other methods of hazard detection, the research in this paper focuses on how to build a unified terrain representation by the terrain features rather than detecting the specific one or several types of hazard obstacles in traditional sense. Computer simulations demonstrates that the method presented in this paper is able to conduct multitype of complex terrain hazard detecting by the terrain feature detected in the visual image obtained from onboard camera during the landing phase. [ABSTRACT FROM AUTHOR]

Military unmanned aerial vehicles (UAVs) are employed in highly dynamic environments and must often adjust their trajectories based on the evolving situation. To operate autonomously and safely, a UAV must be equipped with a path planning module capable of quickly recalculating a feasible and quasi-optimal path in flight while in the event a new obstacle or threat has been detected or simply if the destination point is changed during the mission. To allow for a fast path planning, this paper proposes a parallel implementation of the genetic algorithm on graphics processing unit (GPU). The trajectories are built as series of line segments connected by circular arcs resulting in smooth paths suitable for fixed-wing UAVs. The fitness function we defined takes into account the dynamic constraints of the UAVs and aims to minimize fuel consumption and average flying altitude in order to improve range and avoid detection by enemy radars. This fitness function is also implemented on the GPU and different parallelization strategies were developed and tested for each step of the fitness evaluation. By exploiting the massively parallel architecture of GPUs, the execution time of the proposed path planner was reduced by a factor of 290x compared to a sequential execution on CPU. The path planning module developed was tested using 18 scenarios on six realistic three-dimensional terrains with multiple no-fly zones. We found that the proposed GPU-based path planner was able to find quasi-optimal solutions in a timely fashion allowing in-flight planning. [ABSTRACT FROM AUTHOR]