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Aerospace and Electronic Systems, IEEE Transactions on

Issue 4 • Date OCTOBER 2013

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Displaying Results 1 - 25 of 62
  • Table of Contents

    Publication Year: 2013 , Page(s): c1
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  • [Front inside cover]

    Publication Year: 2013 , Page(s): c2
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  • From the Editor [announcement of new Technical Editor]

    Publication Year: 2013 , Page(s): 1
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  • Low-Complexity Constrained Adaptive Reduced-Rank Beamforming Algorithms

    Publication Year: 2013 , Page(s): 2114 - 2128
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1790 KB) |  | HTML iconHTML  

    A reduced-rank framework with set-membership filtering (SMF) techniques is presented for adaptive beamforming problems encountered in radar systems. We develop and analyze stochastic gradient (SG) and recursive least squares (RLS)-type adaptive algorithms, which achieve an enhanced convergence and tracking performance with low computational cost, as compared with existing techniques. Simulations show that the proposed algorithms have a superior performance to prior methods, while the complexity is lower. View full abstract»

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  • Vision-Based Estimation of Airborne Target Pseudobearing Rate using Hidden Markov Model Filters

    Publication Year: 2013 , Page(s): 2129 - 2145
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2997 KB) |  | HTML iconHTML  

    The problem of estimating pseudobearing rate information of an airborne target based on measurements from a vision sensor is considered. Novel image speed and heading angle estimators are presented that exploit image morphology, hidden Markov model (HMM) filtering, and relative entropy rate (RER) concepts to allow pseudobearing rate information to be determined before (or whilst) the target track is being estimated from vision information. View full abstract»

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  • Equality Constrained Robust Measurement Fusion for Adaptive Kalman-Filter-Based Heterogeneous Multi-Sensor Navigation

    Publication Year: 2013 , Page(s): 2146 - 2157
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2103 KB) |  | HTML iconHTML  

    Constraints can provide additional aids to a multi-sensor integrated navigation system and hence can increase accuracy of the solution and enhance reliability of the system. To integrate the constraints with the data from the sensors, the traditional integration Kalman filter (IKF) needs to be reconstructed. A new algorithm, the so-called constrained adaptive robust integration Kalman filter (CARIKF) is presented, which implements adaptive integration upon the robust direct fusion solution. In the algorithm the raw observations from all heterogeneous sensors are corrected by the pseudoobservations derived from state equality constraint. The posterior covariances of the corrected observations are subsequently estimated upon the robust maximum-likelihood-type estimation (M-estimation) theory. The fusion state and its covariance are solved for all sensors further in the least squares (LS) sense. The pseudoobservations are constructed according to the estimated state and its covariance. They are further combined with the dynamic model of the host platform in an adaptive Kalman filter (AKF), from which a reliable and accurate navigation solution can be then obtained. A state constraint model is proposed upon Newton's forward differential extrapolation numerical method. To demonstrate performance of the CARIKF algorithm, simulations have been conducted in different dynamic and observation scenarios. Several algorithms are compared to evaluate the validity and efficiency of the CARIKF. The results show that the CARIKF is superior to other algorithms and can significantly improve the precision and reliability of the integrated solution. View full abstract»

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  • Oscillator Frequency Offset Impact on Software GPS Receivers and Correction Algorithms

    Publication Year: 2013 , Page(s): 2158 - 2178
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (5394 KB) |  | HTML iconHTML  

    Software-based Global Positioning System (GPS) receivers have been recognized as an effective research platform in recent years. The impact of oscillator frequency offset on hardware receiver and software receiver signal processing is contrasted based on a refined signal model and cross correlation function (CCF) analysis. Several online clock error correction algorithms are presented to produce unbiased measurements and clock error estimates with known and unknown front end frequency plans and with and without signal tracking and navigation solutions for single- and dual-frequency receivers on both static and dynamic platforms. The CCF formulation and the clock correction performance are validated using simulated signals and real single- and dual-frequency GPS data. The raw frequency error measurements with 0.02 s time resolution for an oven controlled crystal oscillator (OCXO) using real GPS signal report an Allan deviation (ADEV) of 1.3E-11 and a standard deviation of 1.56E-11. View full abstract»

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  • Widely Separated MIMO versus Multistatic Radars for Target Localization and Tracking

    Publication Year: 2013 , Page(s): 2179 - 2194
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2259 KB) |  | HTML iconHTML  

    The detection, localization, and tracking performance of multiple input-multiple output (MIMO) radars with widely separated antennas is investigated and compared with that of multistatic radar systems. A multiple-hypothesis (MH)-based algorithm is proposed for multitarget localization for the case where extended targets with multiple spatial reflections become unobservable in certain transmitter-receiver pairs. A particle filter (PF)-based algorithm is then proposed to handle dynamic multitarget tracking. Finally, simulation results are provided to demonstrate the relative capability of MIMO radars in localizing and tracking extended targets under various signal-to-noise ratio (SNR) conditions compared with multistatic radars. View full abstract»

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  • Situation Assessment: An End-to-End Process for the Detection of Objects of Interest

    Publication Year: 2013 , Page(s): 2195 - 2210
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (5014 KB) |  | HTML iconHTML  

    Semiautomatic approaches are developed for wide area situation assessment in near-real-time. The two-step method consists of two granularity levels. The first entity assessment uses a new multi-target tracking (MTT) algorithm (hybridization of Gaussian mixture-Cardinalized probability hypothesis density (GM-CPHD) filter and multiple hypothesis tracker (MHT) with road constraints) on ground moving target indicator (GMTI) data. The situation is then assessed by detecting objects of interest such as convoys with other data types (synthetic aperture radar (SAR), video). These detections are based on Bayesian networks and their credibilistic counterpart. View full abstract»

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  • Rank-Order Adaptive CFAR: Performance Bounds and Efficient Implementation

    Publication Year: 2013 , Page(s): 2211 - 2224
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1938 KB) |  | HTML iconHTML  

    The uniformly most powerful (UMP) rank-order analog to the cell-averaging constant false alarm rate (CA-CFAR) detector is developed for both the single and multi-scan case. The detector is capable of false alarm control in arbitrary noise while achieving maximum detection probability for the case of a Swerling II target in Gaussian noise. Relationships with earlier tests are discussed. A divide-and-conquer method is developed that allows for rapid implementation of a large class of two-sample rank tests. View full abstract»

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  • Terrain Effect Analysis for Cross-Track Stereo SAR Elevation Estimation

    Publication Year: 2013 , Page(s): 2225 - 2234
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    We analyzed the correlation metric used in cross-track stereo SAR elevation estimation. We showed the resulting relationship that arises between false alarms and missed detections, for a range of processing and terrain conditions. We also derived and illustrated constraints between terrain slope, feasible height resolution, and SAR collection geometry. View full abstract»

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  • The ML-PMHT Multistatic Tracker for Sharply Maneuvering Targets

    Publication Year: 2013 , Page(s): 2235 - 2249
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (4832 KB) |  | HTML iconHTML  

    The maximum likelihood probabilistic multi-hypothesis tracker (ML-PMHT) is applied to a benchmark multistatic active sonar scenario with multiple targets, multiple sources, and multiple receivers. We first compare the performance of the tracker on this scenario when it is applied in Cartesian measurement space, a typical implementation for many trackers, against its performance in delay-bearing measurement space, where the measurement uncertainty is more accurately represented. ML-PMHT is a batch tracker, and the motion of a target being tracked must be given a parameterization that describes the motion of the target throughout the batch. In the scenario in which we apply the tracker, the majority of target returns have low amplitudes (i.e., the targets are low-observable), which makes the choice of a batch tracker very appropriate. In prior work, ML-PMHT was implemented with a straight-line parameterization to describe target motion. However, in order to track maneuvering targets, the tracker was implemented in a sliding-batch fashion under the assumption that a maneuvering track could be approximated as a series of short straight lines. Here, we augment the straight-line parameterization by a maneuver-a single course change within the batch-that allows ML-PMHT to follow even sharply maneuvering targets, and we apply it in both Cartesian and delay-bearing measurement space. We also implement this maneuvering-model parameterization with both a fixed batch-length implementation as well as a variable batch-length implementation. Finally, we develop an expression for the Cramer-Rao lower bound (CRLB) for the maneuvering-model parameterization and show that the ML-PMHT tracker with the maneuvering-model parameterization is an efficient estimator. View full abstract»

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  • GPS Spoofing Detection via Dual-Receiver Correlation of Military Signals

    Publication Year: 2013 , Page(s): 2250 - 2267
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2131 KB) |  | HTML iconHTML  

    Cross-correlation of unknown encrypted signals between two Global Navigation Satellite System (GNSS) receivers is used for spoofing detection of publicly-known signals. This detection technique is one of the strongest known defenses against sophisticated spoofing attacks if the defended receiver has only one antenna. The attack strategy of concern overlays false GNSS radio-navigation signals on top of the true signals. The false signals increase in power, lift the receiver tracking loops off of the true signals, and drag the loops and the navigation solution to erroneous but consistent results. Hypothesis testing theory is used to develop a codeless cross-correlation detection method for use in inexpensive, narrowband civilian GNSS receivers. The detection method is instantiated by using the encrypted military Global Positioning System (GPS) P(Y) code on the L1 frequency in order to defend the publicly-known civilian GPS C/A code. Successful detection of spoofing attacks is demonstrated by off-line processing of recorded RF data from narrowband 2.5 MHz RF front-ends, which attenuate the wideband P(Y) code by 5.5 dB. The new technique can detect attacks using correlation intervals of 1.2 s or less. View full abstract»

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  • Direction-of-Arrival Estimation in Subarrays-Based Linear Sparse Arrays with Gain/Phase Uncertainties

    Publication Year: 2013 , Page(s): 2268 - 2280
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1825 KB) |  | HTML iconHTML  

    Sparse arrays are of great interest in practical applications owing to their enlarged array apertures, which enable us to achieve better performance in direction finding. A kind of linear sparse arrays (LSpAs) composed of multiple uniform linear subarrays (ULSAs) with gain/phase uncertainties is considered. The problem of direction-of-arrival (DOA) estimation using such kinds of arrays is addressed. In particular two different cases are studied. In the first case all ULSAs are well calibrated, whereas there are unknown gains/phases among them. Using a new ESPRIT-like method, we show that the DOAs can be estimated in closed form. Interestingly, it is found that the unknown gains/phases can also be estimated in closed form by taking advantage of the subspace principle. In the second case we consider a more general situation where some of the ULSAs themselves are suffering from unknown sensor gain/phase responses. Again, we exploit the ESPRIT algorithm and propose a new approach to DOA and gain/phase estimation using this class of arrays. In our proposed methods the unknown parameters (i.e., DOAs and gains/phases) are estimated in closed form without performing spectral search. Representative numerical results are demonstrated to assess the effectiveness of the methods. View full abstract»

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  • Noise Subspace-Based Iterative Technique for Direction Finding

    Publication Year: 2013 , Page(s): 2281 - 2295
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2236 KB) |  | HTML iconHTML  

    In the area of array signal processing, direction of arrival (DoA) estimation is a widely studied topic. In this estimation process the noise subspace of the received signal covariance matrix is often utilized and obtained through numerical methods. We explicitly derive an algebraic expression of the noise subspace when the number of signal sources present is less than the number of elements of a uniform linear array (ULA). This expression of the noise subspace is then used to formulate a constrained minimization problem to obtain the DoAs of all the sources in a scene in the presence of spatially white noise of identical power. This noise subspace-based estimation (NISE) algorithm iteratively solves for each source's DoA, potentially yielding (depending on the number of iterations) lower complexity than existing DoA estimation algorithms, such as fast root-MUSIC (FRM), while exhibiting performance advantages for a low number of time samples and low signal-to-noise ratio (SNR). The convergence of NISE is then proven mathematically. In addition it is shown how NISE can readily incorporate prior knowledge into the DoA estimation process. View full abstract»

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  • GBAS Reference Receiver Clock Adjustment Effects on Continuity and Integrity Performance

    Publication Year: 2013 , Page(s): 2296 - 2309
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (6533 KB) |  | HTML iconHTML  

    Ground-based augmentation system (GBAS) reference stations provide pseudo-range corrections (PRCs) and range rate corrections (RRCs) for visible GPS satellites along with the standard deviations of the PRC errors (σpr_gnd) and B-values for the reference receivers. When generating PRCs, a GBAS should adjust the reference receiver clock bias to limit the PRC values within a certain range specified by international standards. Since σpr_gnd should reflect the PRC errors accurately for system integrity, it must consider the effect of the clock adjustment procedure. Nevertheless, this has hardly been researched, since it is well known that the clock adjustment does not impact on the user position solution. This paper notices that σpr_gnd is also used for GBAS integrity monitoring functions which are implemented in range domain, not position domain. Thus, the work presented here investigates continuity and integrity performance risk in range domain in case a GBAS estimates σpr_gnd ignoring the clock adjustment procedure and uses it for integrity monitors. The work presented here analyzes the risk by a simulation and proposes strategies for σpr_gnd establishment considering the clock adjustment effects to prevent system performance risk. View full abstract»

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  • Polar-Interval-Based Localization in Mobile Sensor Networks

    Publication Year: 2013 , Page(s): 2310 - 2322
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3145 KB) |  | HTML iconHTML  

    The problem of localization in uncontrolled mobility sensor networks (MSN) is considered. Based on connectivity measurements the problem is solved using polar intervals. Computation is performed, in several polar coordinate systems (PCSs), using both polar coordinates and interval analysis. Position estimates are thus partial rings enclosing the exact solution of the problem. Simulation results corroborate the efficiency of the proposed method compared with existing methods, especially with those handling single coordinate systems. View full abstract»

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  • Multi-Sensor Fusion and Fault Detection using Hybrid Estimation for Air Traffic Surveillance

    Publication Year: 2013 , Page(s): 2323 - 2339
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2812 KB) |  | HTML iconHTML  

    Data fusion for multiple surveillance sensors in air traffic control (ATC) is studied. The goal is to build up software redundancy for better target tracking accuracy and robustness against sensor faults. A set of hybrid estimation algorithms for different sensors is designed to run in parallel for tracking aircraft with changing flight modes. The proposed sensor fusion algorithm combines the estimates from each hybrid estimation algorithm and identifies potential sensor faults. View full abstract»

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  • FEC Systems for Aeronautical Telemetry

    Publication Year: 2013 , Page(s): 2340 - 2352
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2616 KB) |  | HTML iconHTML  

    We consider the design of capacity-approaching forward error correction (FEC) systems for use in the aeronautical telemetry environment. The modulation format is the bandwidth-efficient telemetry-group version of shaped-offset quadrature phase-shift keying (SOQPSK-TG). The FEC codes are a low-density parity-check (LDPC) code and a serially concatenated convolutional code (SCCC). The block structure of the two types of FEC is designed such that the two code words are formatted as similarly as possible. This unified format allows the flexibility of the FEC-encoded signal to be received by legacy test-range assets that are not equipped with FEC¿although no coding gain is realized in such a case. We also show how a wide range of near-optimal SOQPSK demodulators can be paired with the FEC decoders; this includes the most widely deployed SOQPSK demodulator (the so-called symbol-by-symbol (SxS) demodulator), which so far has not been considered for use in FEC applications. In all of our demodulator/decoder designs, we apply techniques that are simple and robust and that fully decouple the demodulator's tasks (e.g., synchronization, filtering) from the decoder's tasks (e.g., path metrics, soft outputs). For both LDPC and SCCC, we show that very attractive system designs can perform within 0.5 dB of optimum, while requiring only a fraction of the complexity of the optimum system. View full abstract»

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  • Channel-Aware Tracking in Multi-Hop Wireless Sensor Networks with Quantized Measurements

    Publication Year: 2013 , Page(s): 2353 - 2368
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1737 KB) |  | HTML iconHTML  

    A channel-aware target tracking approach is proposed for multi-hop sensor networks based on M-bit quantized measurements. For two cases where the fusion center has the knowledge of the instantaneous fading channel gains and where only the knowledge of fading channel statistics is available, particle filtering (PF)-based channel-aware tracking algorithms are developed. Furthermore, the posterior Cramer-Rao lower bounds (PCRLBs) for the tracking filters are derived. The improved tracking accuracy and robustness of the proposed approach are demonstrated through simulations. View full abstract»

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  • Eigen-Template-Based HRR-ATR with Multi-Look and Time-Recursion

    Publication Year: 2013 , Page(s): 2369 - 2385
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3076 KB) |  | HTML iconHTML  

    Automatic target recognition (ATR) using high range resolution (HRR) radar signatures is developed using classical Bayesian multiple hypothesis theory. An eigen-template-based matched filtering (ETMF) algorithm is presented where the templates are formed using the dominant range-space eigenvector of detected HRR training profiles and classification is performed using normalized matched filtering (MF). The proposed approach is extended to multi-look and sequential ATR where new observation profiles are recursively combined probabilistically with previous steps to update ATR results, which is useful for simultaneous recognition and tracking of moving targets. An HRR-specific profile normalization scheme is presented to satisfy matched filter requirements. Classification performance of the proposed method has been compared with a linear least-squares method and hidden Markov model (HMM) approach using MSTAR data collection. View full abstract»

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  • Sparse Grid-Based Nonlinear Filtering

    Publication Year: 2013 , Page(s): 2386 - 2396
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1638 KB) |  | HTML iconHTML  

    The problem of estimating the state of a nonlinear stochastic plant is considered. Unlike classical approaches such as the extended Kalman filter, which are based on the linearization of the plant and the measurement model, we concentrate on the nonlinear filter equations such as the Zakai equation. The numerical approximation of the conditional probability density function (pdf) using ordinary grids suffers from the "curse of dimension" and is therefore not applicable in higher dimensions. It is demonstrated that sparse grids are an appropriate tool to represent the pdf and to solve the filtering equations numerically. The basic algorithm is presented. Using some enhancements it is shown that problems in higher dimensions can be solved with an acceptable computational effort. As an example a six-dimensional, highly nonlinear problem, which is solved in real-time using a standard PC, is investigated. View full abstract»

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  • UAV Path Planning in a Dynamic Environment via Partially Observable Markov Decision Process

    Publication Year: 2013 , Page(s): 2397 - 2412
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3333 KB) |  | HTML iconHTML  

    A path-planning algorithm to guide unmanned aerial vehicles (UAVs) for tracking multiple ground targets based on the theory of partially observable Markov decision processes (POMDPs) is presented. A variety of features of interest are shown to be easy to incorporate into the framework by plugging in the appropriate models, which demonstrates the power and flexibility of the POMDP framework. Specifically, it is shown how to incorporate the following features by appropriately formulating the POMDP action space, transition law, and objective function: 1) control UAVs with both forward acceleration and bank angle subject to constraints; 2) account for the effect of wind disturbance on UAVs; 3) avoid collisions between UAVs and obstacles and among UAVs; 4) track targets while evading threats; 5) track evasive targets; and 6) mitigate track swaps. View full abstract»

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  • Noncoherent Integration for Signal Detection: Analysis Under Model Uncertainties

    Publication Year: 2013 , Page(s): 2413 - 2430
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3248 KB) |  | HTML iconHTML  

    The performance of postdetection integration (PDI) techniques for the detection of Global Navigation Satellite Systems (GNSS) signals in the presence of uncertainties in frequency offsets, noise variance, and unknown data-bits is studied. It is shown that the conventional PDI techniques are generally not robust to uncertainty in the data-bits and/or the noise variance. Two new modified PDI techniques are proposed, and they are shown to be robust to these uncertainties. The receiver operating characteristics (ROC) and sample complexity performance of the PDI techniques in the presence of model uncertainties are analytically derived. It is shown that the proposed methods significantly outperform existing methods, and hence they could become increasingly important as the GNSS receivers attempt to push the envelope on the minimum signal-to-noise ratio (SNR) for reliable detection. View full abstract»

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  • A Fast and Efficient Clutter Rejection Algorithm for SAR Imagery

    Publication Year: 2013 , Page(s): 2431 - 2439
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1390 KB) |  | HTML iconHTML  

    A clutter rejection scheme is proposed for synthetic aperture radar (SAR) imagery based on two-stage two-dimensional principal component analysis (two-stage 2DPCA) followed by a bipolar eigenspace separation transformation (BEST) and a multilayer perceptron (MLP). For this, we have examined and analyzed four different algorithms. They are based on principal component analysis (PCA) both in one dimension (conventional PCA) and in two dimension with three different forms (2DPCA, alternative 2DPCA and two-stage 2DPCA), followed by BEST and MLP in each case. Feature extraction in different cases is carried out using respective PCA scheme. Each algorithm uses the BEST to further reduce dimensionality and enhance the generalization capability of the classifier. Classification between target chips and clutter chips is finally made through an MLP classifier. Experimental results on MSTAR public release database of SAR imagery are presented. Comparison of all the 2DPCA algorithms with an existing technique shows improvement both in performance and time. Moreover, all the 2DPCA algorithms compute eigenvectors and eigenvalues of image covariance matrix accurately and very efficiently with respect to time, and further reduces the effect of noise better than that in the case of PCA. Comparison reveals the fact that two-stage 2DPCA-based algorithm is the best (both in performance and time) between all algorithms. View full abstract»

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Aims & Scope

IEEE Transactions on Aerospace and Electronic Systems focuses on the equipment, procedures, and techniques applicable to the organization, installation, and operation of functional systems designed to meet the high performance requirements of earth and space systems.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Lance Kaplan
Army Research Laboratory