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Aerospace and Electronic Systems, IEEE Transactions on

Issue 3 • Date July 2006

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  • IEEE Transactions on Aerospace and Electronic Systems

    Page(s): c1
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    Freely Available from IEEE
  • IEEE Aerospace and Electronic Systems Society

    Page(s): c2
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    Freely Available from IEEE
  • From tne Editor-in-Chief

    Page(s): 769
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  • Resolution of signal sources via spectral moment estimation

    Page(s): 770 - 777
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1745 KB) |  | HTML iconHTML  

    In different practical situations it is desired to estimate the number of signal sources and their positions in space or in frequency domain. The first problem is known as the detection or the order estimation and the second one as the resolution. For the resolution problem techniques such as nonlinear least squares (NLSM), high-order Yule-Walker method (HOYW), multiple signal classification (MUSIC), Pisarenko harmonic retrieval method, min-norm method, estimation of signal parameters by rotational invariance technique (ESPRIT), were proposed (Marple, 1987 and Stoica and Moses, 1997). All these high-resolution methods are based on the analysis of the signal covariance matrix. But the covariance matrix is not the only choice to represent the signal spectrum. In different applications (weather radars, synthetic aperture radar (SAR) signal processing, ultrasound imaging in medicine, atmospheric turbulence measurements) the signal spectrum can be modeled through its algebraic moments. Recently a number of efficient nonparametric methods have been proposed to estimate the algebraic spectral moments (Monakov, 1999). The presented paper is an attempt to solve the direction of arrival (DOA) problem via estimation of the algebraic spectral moments. A method proposed in the article is comparable in its accuracy with the MUSIC method. At the same time its computational burden is much lower. The method permits to estimate the signal power of sources easily to complete the full spectral line analysis. Additionally the method shows good robustness in situations when signal sources have noticeable spatial extend View full abstract»

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  • Track labeling and PHD filter for multitarget tracking

    Page(s): 778 - 795
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2763 KB) |  | HTML iconHTML  

    Multiple target tracking requires data association that operates in conjunction with filtering. When multiple targets are closely spaced, the conventional approaches (as, e.g., MHT/assignment) may not give satisfactory results. This is mainly because of the difficulty in deciding what the number of targets is. Recently, the probability hypothesis density (PHD) filter has been proposed and particle filtering techniques have been developed to implement the PHD filter. In the particle PHD filter, the track labeling problem is not considered, i.e., the PHD is obtained only for a frame at a time, and it is very difficult to perform the multipeak extraction, particularly in high clutter environments. A track labeling method combined with the PHD approach, as well as considering the finite resolution, is proposed here for multitarget tracking, i.e., we keep a separate tracker for each target, use the PHD in the resolution cell to get the estimated number and locations of the targets at each time step, and then perform the track labeling ("peak-to-track" association), whose results can provide information for PHD peak extraction at the next time step. Besides, by keeping a separate tracker for each target, our approach provides more information than the standard particle PHD filter. For example, in group target tracking, if we are interested in the motion of a specific target, we can track this target, which is not possible for the standard particle PHD filter, since the standard particle PHD filter does not keep track labels. Using our approach, multitarget tracking can be performed with automatic track initiation, maintenance, spawning, merging, and termination View full abstract»

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  • Global magnetic attitude control of spacecraft in the presence of gravity gradient

    Page(s): 796 - 805
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1707 KB) |  | HTML iconHTML  

    The problem of Earth-pointing attitude control for a spacecraft with magnetic actuators is addressed and a novel approach to the problem is proposed, which guarantees almost global closed loop stability of the desired relative attitude equilibrium for the spacecraft. Precisely, a proportional derivative (PD)-like state feedback control law is employed together with a suitable adaptation mechanism for the controller gain. Simulation results are presented, which illustrate the performance of the proposed control law View full abstract»

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  • Linear filtering approaches for phase calibration of airborne arrays

    Page(s): 806 - 824
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2279 KB) |  | HTML iconHTML  

    Phase calibration of a large fluctuating millimeter-wave airborne antenna array is considered. The technique exploits properties of the correlation of the measured voltages arising from clutter returns at adjacent or nearby element pairs. The proposed calibration algorithm trades smoothing of the observations to reduce random errors with the ability to track the time-varying calibration phase. Algorithm performance is considered for an arbitrary linear filter, which generalizes previous work on analogous pulse-pair problems, and the results are used to choose optimal filter parameters. Numerical results are provided for a field experiment employing a 32-element Ku-band antenna array View full abstract»

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  • Nonlinear control and stability analysis of spacecraft attitude recovery

    Page(s): 825 - 845
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3344 KB) |  | HTML iconHTML  

    The problem of automated attitude recovery of rigid and flexible spacecraft is investigated using feedback linearization control and a novel approach for generating the control error signal based on quaternion addition. The attitude and flexible dynamics equations for a class of spacecraft is presented. The resulting nonlinear and coupled equations of the system are implemented into a high-fidelity user-friendly simulation environment. The simulator is used for the investigation of attitude recovery of flexible spacecraft using the feedback linearization approach. Since the flexible spacecraft is underactuated, the input-output linearization technique was specifically used to break up the system into two distinct parts, namely 1) an external linearizable system for which a linear controller can be easily implemented, and 2) an internal nonlinear unobservable system for which the associated zero dynamics is shown to be asymptotically stable for two representative cases. The overall closed-loop stability of the flexible spacecraft is analyzed rigorously and shown to be asymptotically stable using Lyapunov's method View full abstract»

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  • On hierarchical tracking for the real world

    Page(s): 846 - 850
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (179 KB) |  | HTML iconHTML  

    Several information processing configurations for hierarchical tracking and their performances are described in a concise manner, and the selection of one of them is discussed. It is shown that the performance of the "track-to-track fusion without memory" configuration, which, while suboptimal, is simple from the point of view of both computation and communication requirements, is remarkably close to the optimum View full abstract»

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  • Near lossless data compression onboard a hyperspectral satellite

    Page(s): 851 - 866
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (4222 KB) |  | HTML iconHTML  

    To deal with the large volume of data produced by hyperspectral sensors, the Canadian Space Agency (CSA) has developed and patented two near lossless data compression algorithms for use onboard a hyperspectral satellite: successive approximation multi-stage vector quantization (SAMVQ) and hierarchical self-organizing cluster vector quantization (HSOCVQ). This paper describes the two compression algorithms and demonstrates their near lossless feature. The compression error introduced by the two compression algorithms was compared with the intrinsic noise of the original data that is caused by the instrument noise and other noise sources such as calibration and atmospheric correction errors. The experimental results showed that the compression error was not larger than the intrinsic noise of the original data when a test data set was compressed at a compression ratio of 20:1. The overall noise in the reconstructed data that contains both the intrinsic noise and the compression error is even smaller than the intrinsic noise when the data is compressed using SAMVQ. A multi-disciplinary user acceptability study has been carried out in order to evaluate the impact of the two compression algorithms on hyperspectral data applications. This paper briefly summarizes the evaluation results of the user acceptability study. A prototype hardware compressor that implements the two compression algorithms has been built using field programmable gate arrays (FPGAs) and benchmarked. The compression ratio and fidelity achieved by the hardware compressor are similar to those obtained by software simulation View full abstract»

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  • Reliability comparison of matrix and other converter topologies

    Page(s): 867 - 875
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1848 KB) |  | HTML iconHTML  

    Several rectifier-inverter and matrix converter topologies suitable for aerospace applications are compared, and their reliability is predicted. The military handbook MIL-HDBK-217F guidelines have been used to predictreliability. The matrix converter has several attractive features for aerospace applications such as potential size and weight savings. Although the matrix converter has a higher number of semiconductor switches, they are subjected to a lower voltage stress, which decreases their failure rate. This results in the reliability indicators of the different converter topologies being very similar View full abstract»

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  • Performance analysis of conformal conical arrays for airborne vehicles

    Page(s): 876 - 890
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3460 KB) |  | HTML iconHTML  

    Conformal array apertures have great potential for providing high performance, low weight systems with little or no impact to the aerodynamic design of the air vehicle. A performance analysis of conformal conical arrays for a national airborne radar application is presented. The conical array geometry is chosen for its similarity to an aircraft or missile nosecone. Performance capabilities are analyzed for a number of antenna performance parameters including scan volume, sidelobe levels, grating lobes, beamwidth, directivity, element count, and cross-polarization View full abstract»

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  • Multistatic adaptive pulse compression

    Page(s): 891 - 903
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1894 KB) |  | HTML iconHTML  

    A new technique denoted as multistatic adaptive pulse compression (MAPC) is introduced which exploits recent work on adaptive pulse compression (APC) in order to jointly separate and pulse compress the concurrently received return signals from K proximate multistatic radars operating (i.e., transmitting) within the same spectrum. For the return signal from a single pulse of a monostatic radar, APC estimates the particular receive filter for a given range cell in a Bayesian sense reiteratively by employing the matched filter estimates of the surrounding range cell values as a priori knowledge in order to place temporal (i.e., range) nulls at the relative ranges occupied by large targets and thereby suppress range sidelobes to the level of the noise. The MAPC approach generalizes the APC concept by jointly estimating the particular receive filter for each range cell associated with each of several concurrently-received radar return signals occupying the same spectrum. As such, MAPC is found to enable shared-spectrum multistatic operation and is shown to yield substantial performance improvement in the presence of multiple spectrum-sharing radars as compared with both standard matched filters and standard least-squares mismatched filters View full abstract»

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  • Doppler visibility of coherent ultrawideband random noise radar systems

    Page(s): 904 - 916
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (4174 KB) |  | HTML iconHTML  

    Random noise radar has recently been used in a variety of imaging and surveillance applications. These systems can be made phase coherent using the technique of heterodyne correlation. Phase coherence has been exploited to measure Doppler and thereby the velocity of moving targets. The Doppler visibility, i.e., the ability to extract Doppler information over the inherent clutter spectra, is constrained by system parameters, especially the phase noise generated by microwave components. Our paper proposes a new phase noise model for the heterodyne mixer as applicable for ultrawideband (UWB) random noise radar and for the local oscillator in the time domain. The Doppler spectra are simulated by including phase noise contamination effects and compared with our previous experimental results. A genetic algorithm (GA) optimization routine is applied to synthesize the effects of a variety of parameter combinations to derive a suitable empirical formula for estimating the Doppler visibility in dB. According to the phase noise analysis and the simulation results, the Doppler visibility of UWB random noise radar depends primarily on the following parameters: 1) the local oscillator (LO) drive level of the receiver heterodyne mixer, 2) the saturation current in the receiver heterodyne mixer, 3) the bandwidth of the transmit noise source, and 4) the target velocity. Other parameters such as the carrier frequency of the receiver LO and the loaded quality factor of the LO have a small effect over the range of applicability of the model and are therefore neglected in the model formulation. The Doppler visibility curves generated from this formula match the simulation results very well over the applicable parameter range within 1 dB. Our model may therefore be used to quickly estimate the Doppler visibility of random UWB noise radars for trade-off analysis View full abstract»

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  • Effect of earth's rotation and range foldover on space-based radar performance

    Page(s): 917 - 932
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (4280 KB) |  | HTML iconHTML  

    Space-based radar (SBR) by virtue of its motion generates a Doppler frequency component to the clutter return from any point on the Earth as a function of the SBR-Earth geometry. The effect of the rotation of the Earth around its own axis also adds an additional component to this Doppler frequency. The overall effect of the rotation of the Earth on the Doppler turns out to be two correction factors in terms of a crab angle affecting the azimuth angle, and a crab magnitude scaling the Doppler magnitude of the clutter patch. Interestingly, both these quantities depend only on the SBR orbit inclination and its latitude and not on the location of the clutter patch of interest. Further, the crab angle has maximum effect for an SBR on a polar orbit that is above the equator. The crab magnitude, on the other hand, peaks for an SBR on an equatorial orbit. Together with the range foldover phenomenon, their overall effect is to generate Doppler spread/splitting resulting in wider clutter notches that degrade the clutter nulling performance of adaptive processing techniques. A detailed performance analysis and methods to minimize these effects are discussed here View full abstract»

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  • Family of multicarrier bi-phase radar signals represented by ternary arrays

    Page(s): 933 - 953
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    A K times L ternary array, comprised of the elements {0, 1, - 1}, with some unique features, represents a multicarrier radar signal with favorable autocorrelation and ambiguity functions. Constructing such an array using Galois fields is described. As in a Costas binary array, only one frequency is transmitted at any time slot, but in our array the same frequency is repeated in several time slots, yielding a signal with considerably larger pulse compression than a Costas signal that uses the same number of frequencies View full abstract»

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  • Optimized one-cycle control in photovoltaic grid connected applications

    Page(s): 954 - 972
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (6069 KB) |  | HTML iconHTML  

    The use of one-cycle control (OCC) for maximum power point tracking (MPPT) and power factor correction (PFC) in grid connected photovoltaic (PV) applications is discussed. Circuit and operating parameters of the one cycle-based controller of a cost-effective single-stage inverter are optimized in order to obtain the best performances of the system under different irradiance levels. Firstly, design constraints are formulated which allow to get a very efficient OCC operation in terms of power extracted from the PV array, stability, and PFC. Afterwards, such constraints are used to perform the parametric optimization of the one cycle controller by means of suitable heuristic approaches. Various selection criteria of the best parameters set under different conditions are discussed and applied. Finally, a customized perturb and observe (P&O) control is applied to the optimized one cycle controlled single-stage inverter in order to perform a real MPPT in presence of varying irradiance conditions. Subjects described here are covered by the Italian Patent Application SA2005A000014-13.07.2005 and PCT Application PCT/IT2005/000747-20.12.2005 View full abstract»

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  • Stochastic constraints for efficient image correspondence search

    Page(s): 973 - 982
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1803 KB) |  | HTML iconHTML  

    The navigation state (position, velocity, and attitude) can be determined using optical measurements from an imaging sensor pointed toward the ground. Extracting navigation information from an image sequence depends on tracking the location of stationary objects in multiple images, which is generally termed the correspondence problem. This is an active area of research and many algorithms exist which attempt to solve this problem by identifying a unique feature in one image and then searching subsequent images for a feature match. In general, the correspondence problem is plagued by feature ambiguity, temporal feature changes, and occlusions which are difficult for a computer to address. Constraining the correspondence search to a subset of the image plane has the dual advantage of increasing robustness by limiting false matches and improving search speed. A number of ad hoc methods to constrain the correspondence search have been proposed in the literature. A rigorous stochastic projection method is developed here which constrains the correspondence search space by incorporating a priori knowledge of the aircraft navigation state using inertial measurements and a statistical terrain model. The stochastic projection algorithm is verified using Monte Carlo simulation and flight data. The constrained correspondence search area is shown to accurately predict the pixel location of a feature with an arbitrary level of confidence, thus promising improved speed and robustness of conventional algorithms View full abstract»

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  • Knowledge-aided signal processing: a new paradigm for radar and other advanced sensors

    Page(s): 983 - 996
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2419 KB) |  | HTML iconHTML  

    Recently, significant progress has been made in the development of physics-based, knowledge-aided (KA) signal processing strategies supported by improvements in real-time embedded computing architectures. These developments provide designers of advanced sensor systems an unprecedented degree of flexibility when implementing next generation adaptive sensor systems. In the case of radar, this has been manifested in the first ever, real-time, KA space-time adaptive processing (KA-STAP) system for advanced clutter/interference suppression. This paper provides exemplars of real-world effects giving rise to the need for "intelligent" adaptation schemes and overviews the KA approach to sensor signal processing in some detail. Moreover, we survey a collection of papers describing recent KA sensor research that follow in this issue View full abstract»

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  • Improved clutter mitigation performance using knowledge-aided space-time adaptive processing

    Page(s): 997 - 1009
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2566 KB) |  | HTML iconHTML  

    This paper presents a framework for incorporating knowledge sources directly in the space-time beamformer of airborne adaptive radars. The algorithm derivation follows the usual linearly-constrained minimum-variance (LCMV) space-time beamformer with additional constraints based on a model of the clutter covariance matrix that is computed using available knowledge about the operating environment. This technique has the desirable property of reducing sample support requirements by "blending" the information contained in the observed radar data and the a priori knowledge sources. Applications of the technique to both full degree of freedom (DoF) and reduced DoF beamformer algorithms are considered. The performance of the knowledge-aided beam forming techniques are demonstrated using high-fidelity simulated X-band radar data View full abstract»

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  • Spectral-domain covariance estimation with a priori knowledge

    Page(s): 1010 - 1020
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1511 KB) |  | HTML iconHTML  

    A knowledge-aided spectral-domain approach to estimating the interference covariance matrix used in space-time adaptive processing (STAP) is proposed. Prior knowledge of the range-Doppler clutter scene is used to identify geographic regions with homogeneous scattering statistics. Then, minimum-variance spectral estimation is used to arrive at a spectral-domain clutter estimate. Finally, space-time steering vectors are used to transform the spectral-domain estimate into a data-domain estimate of the clutter covariance matrix. The proposed technique is compared with ideal performance and to the fast maximum likelihood technique using simulated results. An investigation of the performance degradation that can occur due to various inaccurate knowledge assumptions is also presented View full abstract»

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  • An approach to knowledge-aided covariance estimation

    Page(s): 1021 - 1042
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3628 KB) |  | HTML iconHTML  

    This paper introduces a parametric covariance estimation scheme for use with space-time adaptive processing (STAP) methods operating in heterogeneous clutter environments. The approach blends both a priori knowledge and data observations within a parameterized model to capture instantaneous characteristics of the cell under test (CUT) and reduce covariance errors leading to detection performance loss. We justify this method using both measured and synthetic data. Performance potential for the specific operating conditions examined herein include: 1) averaged behavior within roughly 2 dB of the optimal filter, 2) 1 dB improvement in exceedance characteristic relative to the optimal filter, highlighting improved instantaneous capability, and 3) impervious ness to corruptive target-like signals in the secondary data (no additional signal-to-interference-plus-noise ratio (SINK) loss, compared with 10 dB or greater loss for the standard STAP implementation), with corresponding detections comparable to the optimal filter case View full abstract»

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  • Stap using knowledge-aided covariance estimation and the fracta algorithm

    Page(s): 1043 - 1057
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (4126 KB) |  | HTML iconHTML  

    In the airborne space-time adaptive processing (STAP) setting, a priori information via knowledge-aided covariance estimation (KACE) is employed in order to reduce the required sample support for application to heterogeneous clutter scenarios. The enhanced FRACTA (FRACTA.E) algorithm with KACE as well as Doppler-sensitive adaptive coherence estimation (DS-ACE) is applied to the KASSPER I & II data sets where it is shown via simulation that near-clairvoyant detection performance is maintained with as little as 1/3 of the normally required number of training data samples. The KASSPER I & II data sets are simulated high-fidelity heterogeneous clutter scenarios which possess several groups of dense targets. KACE provides a priori information about the clutter covariance matrix by exploiting approximately known operating parameters about the radar platform such as pulse repetition frequency (PRF), crab angle, and platform velocity. In addition, the DS-ACE detector is presented which provides greater robustness for low sample support by mitigating false alarms from undernulled clutter near the clutter ridge while maintaining sufficient sensitivity away from the clutter ridge to enable effective target detection performance View full abstract»

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  • Design and analysis of a knowledge-aided radar detector for doppler processing

    Page(s): 1058 - 1079
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (4034 KB) |  | HTML iconHTML  

    In this paper we discuss the combined use of a priori information and adaptive signal processing techniques for the design and the analysis of a knowledge-aided (KA) radar receiver for Doppler processing. To this end, resorting to the generalized likelihood function (GLF) criterion (both one-step and two-step), we design and assess data-adaptive procedures for the selection of training data. Then we introduce a KA radar detector composed of three elements: a geographic-map-based data selector, which exploits some a priori information concerning the topography of the observed scene, a data-adaptive training selector which removes dynamic outliers from the training data, and an adaptive radar detector which performs the final decision about the target presence. The performance of the KA algorithm is analyzed both on simulated as well as on real radar data collected by the McMaster University IPIX radar. The results show that the new KA system achieves a satisfactory performance level and can outperform some previously proposed adaptive detection schemes View full abstract»

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  • Implementing digital terrain data in knowledge-aided space-time adaptive processing

    Page(s): 1080 - 1099
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (5483 KB) |  | HTML iconHTML  

    Many practical problems arise when implementing digital terrain data in airborne knowledge-aided (KA) space-time adaptive processing (STAP). This paper addresses these issues and presents solutions with numerical implementations. In particular, using digital land classification data and digital elevation data, techniques are developed for registering these data with radar return signals, correcting for Doppler and spatial misalignments, adjusting for antenna gain, characterizing clutter patches for secondary data selection, and ensuring independent secondary data samples. These techniques are applied to select secondary data for a single-bin post-Doppler STAP algorithm using multi-channel airborne radar measurement (MCARM) program data. Results with the KA approach are compared with those obtained using the standard sliding window method for choosing secondary data. These results illustrate the benefits of using terrain information, a priori data about the radar, and the importance of statistical independence when selecting secondary data for improving STAP performance 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.

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Meet Our Editors

Editor-in-Chief
Lance Kaplan
Army Research Laboratory