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Aerospace and Electronic Systems, IEEE Transactions on

Issue 2 • Date Apr 2001

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Displaying Results 1 - 25 of 34
  • MTI data clustering and formation recognition

    Page(s): 524 - 537
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1464 KB) |  | HTML iconHTML  

    Image exploitation technology approaches have generally focused on the detection and spatial analysis of stationary groups of objects on the ground using various sensors. While spatial arrangement is clearly necessary in analyzing military formations, it is usually not sufficient. Typically the arrangement must be examined within some context in order to interpret a pattern of deployment. For moving objects the spatial arrangement of the group relative to the direction of motion is key to recognizing the formation. By examining ground moving target indicator (MTI) radar data over time, motion can be inferred and used to establish a context for interpreting the spatial arrangement of the data. New techniques that exploit the multitemporal nature of MTI data are described. The first is a space-time clustering technique that locates compact groups of objects that persist in time. The technique Is an application of Marr and Hildreth's edge detection methodology to the dual problem of region segmentation, or more accurately, volumetric segmentation of space-time. The second technique is based on the use of the Hough transform for recognizing moving formations such as columns, wedges, and lines abreast by analyzing the shape of clustered MTI detections (specifically the orientation of linear arrangements within the group) with respect to their direction of motion. Preliminary results from simulated MTI data sets are presented View full abstract»

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  • Validation of windblown radar ground clutter spectral shape

    Page(s): 538 - 548
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1292 KB) |  | HTML iconHTML  

    We investigate the robustness of the linear matched filter (MF) operating in a Gaussian environment in the presence of a mismatch between the design clutter-power spectral density (PSD) shape and the actual one. The Gaussian, the power-law (PL), and the double-exponential spectral models have been considered with the goal of investigating which one fits best for windblown foliage. We analyze the MF performance in terms of improvement factor, probability of false alarm, and probability of detection by making use of the theoretical models and measured X-band ground clutter data. The numerical results validate the double-exponential spectral model for windblown foliage by showing that the differences in performance prediction between using measured clutter data and modeled clutter data of various spectral shapes (viz., Gaussian, FL, and double-exponential) are minimized when the spectral model employed is of double-exponential shape View full abstract»

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  • Effects of finite weight resolution and calibration errors on the performance of adaptive array antennas

    Page(s): 549 - 562
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1584 KB) |  | HTML iconHTML  

    Adaptive antennas are now used to increase the spectral efficiency in mobile telecommunication systems. A model of the received carrier-to-interference plus noise ratio (CINR) in the adaptive antenna beamformer output is derived, assuming that the weighting units are implemented in hardware, The finite resolution of weights and calibration is shown to reduce the CINR. When hardware weights are used, the phase or amplitude step size in the weights can be so large that it affects the maximum achievable CINR. It is shown how these errors makes the interfering signals “leak” through the beamformer and we show how the output CINR is dependent on power of the input signals. The derived model is extended to include the limited dynamic range of the receivers, by using a simulation model. The theoretical and simulated results are compared with measurements on an adaptive array antenna testbed receiver, designed for the GSM-1800 system. The theoretical model was used to find the performance limiting part in the testbed as the 1 dB resolution in the weight magnitude. Furthermore, the derived models are used in illustrative examples and can be used for system designers to balance the phase and magnitude resolution and the calibration requirements of future adaptive array antennas View full abstract»

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  • Analysis of single-platform passive emitter location with terrain data

    Page(s): 495 - 507
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1228 KB) |  | HTML iconHTML  

    Frequency measurements made at a moving platform can be used to locate an emitter. An error ellipsoid analysis is used to compare the performance under three levels of a priori information on the emitter's altitude: (1) no knowledge, (2) terrain data, and (3) complete knowledge of the emitter's altitude. The analysis is performed for two simple platform paths that provide frequency measurements that are approximately time reversed versions of one another. When no a priori knowledge is available there is little difference between the performance when the platform maneuvers on a concave circular path or on a convex circular path and the performance depends very Little on the platform altitude. However, when some a priori altitude information is available the performance is markedly different on the two paths and is highly dependent on the platform altitude. Thus, this analysis provides the unexpected result that for seemingly similar platform paths, the performance can vary markedly when the emitter altitude is assumed known. Also, an interesting result is that for some cases it is possible to achieve better x-y accuracy when using terrain data than when the emitter's z location is known, because the terrain data provides terrain slope information. These cases are characterized in terms of the terrain slope at the emitter View full abstract»

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  • Support vector machines for SAR automatic target recognition

    Page(s): 643 - 654
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1140 KB) |  | HTML iconHTML  

    Algorithms that produce classifiers with large margins, such as support vector machines (SVMs), AdaBoost, etc, are receiving more and more attention in the literature. A real application of SVMs for synthetic aperture radar automatic target recognition (SAR/ATR) is presented and the result is compared with conventional classifiers. The SVMs are tested for classification both in closed and open sets (recognition). Experimental results showed that SVMs outperform conventional classifiers in target classification. Moreover, SVMs with the Gaussian kernels are able to form a local “bounded” decision region around each class that presents better rejection to confusers View full abstract»

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  • Adaptive digital beamforming for angle estimation in jamming

    Page(s): 508 - 523
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1636 KB) |  | HTML iconHTML  

    A radar digital beamforming (DBF) architecture and processing algorithm is described for nulling the signal from a mainlobe electronic jammer and multiple sidelobe electronic jammers while maintaining monopulse angle estimation accuracy on the target. The architecture consists of a sidelobe jamming (SLJ) cancelling adaptive array (AA) followed by a mainlobe jamming (MLJ) canceller. A mainlobe maintenance (MLM) technique or constrained adaptation during the sidelobe cancellation process is imposed so that the results of the SLJ cancellation process do not distort the subsequent mainlobe cancellation process. The SLJ signals and the MLJ signals are thus cancelled sequentially in separate processes. This technique was developed for improving radar processing in determining the angular location of a target, and specifically for improving the monopulse technique by maintaining the accuracy of the target echo monopulse ratio in the presence of electronic jamming by adaptive suppression of the jamming signals before forming the monopulse sum and difference beams View full abstract»

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  • Fuzzy-logic-based CLOS guidance law design

    Page(s): 719 - 727
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (604 KB) |  | HTML iconHTML  

    A fuzzy-logic-based command to line-of-sight (CLOS) guidance law is proposed. In this design, the guidance problem is converted to the tracking problem. Then the fuzzy controller is designed to achieve satisfactory tracking performance. Meanwhile, an on-line tuning factor is introduced to speed up the convergence of tracking error and to reduce the miss distance. Besides, a CLOS compensator is designed to eliminate the pseudo-CLOS effect. Simulation results for different engagement scenarios illustrate the validity of the proposed guidance law View full abstract»

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  • Recursive method for optimum GPS satellite selection

    Page(s): 751 - 754
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (336 KB) |  | HTML iconHTML  

    The author addresses the problem of selecting an optimum n-satellite subset from m visible satellites (m>n). The optimality criteria is minimum geometric dilution of precision (GDOP) subject to the integrity constraint. To solve this problem an efficient algorithm is developed using a revolving door method and matrix inversion lemma. The revolving door method generates each n-subset from its immediate predecessor by deleting some single element and adjoining some other single element. Then using the matrix inversion lemma, the GDOP for each new n-subset is recursively calculated from the incoming and outgoing elements. The matrix inversion lemma is also used to check the satisfaction of the integrity constraint View full abstract»

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  • On-line gain-tuning IP controller using RFNN

    Page(s): 655 - 670
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1236 KB) |  | HTML iconHTML  

    In this study an integral-proportional (IP) controller with on-line gain-tuning using a recurrent fuzzy neural network (RFNN) is proposed to control the mover position of a permanent magnet linear synchronous motor (PMLSM) servo drive system. The structure and operating principle of the PMLSM are first described in detail. A field-oriented control PMLSM servo drive is then introduced. After that, an IP controller with on-line gain tuning using an RFNN is proposed to control the mover of the PMLSM for achieving high-precision position control with robustness. The backpropagation algorithm is used to train the RFNN on line. Moreover to guarantee the convergence of tracking error for the periodic step-command tracking, analytical methods based on a discrete-type Lyapunov function are proposed to determine the varied learning rates of the RFNN. Furthermore, the proposed control system is implemented in a PC-based computer control system, Finally, the effectiveness of the proposed PMLSM servo drive system is demonstrated by some simulated and experimental results. Accurate tracking response and superior dynamic performance can be obtained due to the powerful on-line learning capability of the RFNN. In addition, the proposed on-line gain-tuning servo drive system is robust with regard to parameter variations and external disturbances View full abstract»

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  • Receiver operating characteristics for the coherent UWB random noise radar

    Page(s): 586 - 594
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (656 KB) |  | HTML iconHTML  

    An ultrawideband (UWB) random-noise radar operating in the 1-2 GHz frequency band has been developed and held-tested at a 200 m range at the University of Nebraska. A unique heterodyne correlation technique based on a delayed transmitted waveform using a photonic delay line has been used to inject coherence within this system. The performance of this radar, assuming a point target, has been investigated from a statistical point of view by developing the theoretical basis for the system's receiver operating characteristics (ROC). Explicit analytical expressions for the joint probability density function (pdf) of the in-phase (I) and quadrature (Q) components of the receiver output have been derived under the assumption that the input signals are partially correlated Gaussian processes. The pdf and the complementary cumulative distribution function (cdf) for the envelope of the receiver output are also derived. These expressions are used to relate the probability of detection (Pd) to the probability of false alarm (Pf ) for different numbers of integrated samples, and the results are analyzed View full abstract»

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  • Monopulse DOA estimation of two unresolved Rayleigh targets

    Page(s): 452 - 469
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1476 KB) |  | HTML iconHTML  

    This paper provides for new approaches to the processing of unresolved measurements as two direction-of-arrival (DOA) measurements for tracking closely spaced targets rather than the conventional single DOA measurement of the centroid. The measurements of the two-closely spaced targets are merged when the target echoes are not resolved in angle, range, or radial velocity (i.e., Doppler processing). The conditional Cramer Rao lower bound (CRLB) is developed for the DOA estimation of two unresolved Rayleigh targets using a standard monopulse radar. Then the modified CRLB is used to give insight into the boresight pointing for monopulse DOA estimation of two unresolved targets. Monopulse processing is considered for DOA estimation of two unresolved Rayleigh targets with known or estimated relative radar cross section (RCS). The performance of the DOA estimator is studied via Monte Carlo simulations and compared with the modified CRLB View full abstract»

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  • FPGA-based adaptive tracking estimation computer

    Page(s): 699 - 706
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (604 KB) |  | HTML iconHTML  

    We describe an FPGA-based adaptive tracking estimation computer (FATEC) for a multiple target tracking (MTT) radar system. Its design is centered around a small processor core customized according to the requirements of tracking application, to run the main control program and provide software flexibility, with a number of tracking algorithms (models) implemented in hardware-type functional units, in order to meet the timing requirements of the application. The FATEC approach provides combination of software flexibility, hardware efficiency, and functional adaptivity of implementation of application-specific computers for the other applications of a similar type, enabling various partitioning options between the software and the hardware parts of the solution View full abstract»

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  • Alternate forms of the PWM switch model in discontinuous conduction mode [DC-DC converters]

    Page(s): 754 - 758
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (396 KB) |  | HTML iconHTML  

    A pulsewidth-modulated (PWM) DC-DC converter enters discontinuous conduction mode (DCM) as its inductor current attempts to reverse direction, but cannot do so because of switch implementation, and remains at zero in the last interval of each switching period. Three equivalent three-terminal nonlinear transformers are described as the models for the PWM switch in a DCM converter, each having one of the three terminals serving as the common terminal. Each model facilitates the analysis of those corresponding converters in which the PWM switch terminal corresponds to the common transformer terminal is DC-grounded. Examples are given to demonstrate how the models are used to derive the DCM criteria, and the ideal and nonideal voltage gains for the buck-boost, buck, and boost DC-DC converters. The results predicted by the models agree with those reported and verified in the literature View full abstract»

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  • Output voltage bounds of a three-phase boost rectifier

    Page(s): 671 - 678
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (568 KB) |  | HTML iconHTML  

    A general closed-form duty cycle control law is derived based on the linear combination of two sets of continuous duty cycle control laws. From this general solution one can generate infinitely many pulsewidth modulation (PWM) control strategies to achieve the same ideal performance. Then, from the resulting closed-form solution, a general explicit lower bound and a general explicit upper bound of the output dc voltage are derived. Besides the academic interests, these bounds are very useful practically as a convenient guideline for helping quickly design the three-phase boost rectifier. Finally, some illustrative examples are given and some experimental results provided for verifying the derived bounds View full abstract»

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  • Nonlinear filtering: A hybrid approximation scheme

    Page(s): 470 - 480
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1088 KB) |  | HTML iconHTML  

    This paper is concerned with nonlinear filtering schemes for systems which allow non-Gaussian noise. Using the most probable trajectory (MPT) approach, a finite-dimensional recursive hybrid filtering scheme is derived. By appropriately selecting a switching process, a linear hybrid system can be obtained that approximates the original nonlinear system. Then the MPT approach is used to obtain the hybrid filtering schemes for the nonlinear systems. Numerical experiments are carried out and reported View full abstract»

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  • Multiaspect classification of airborne targets via physics-based HMMs and matching pursuits

    Page(s): 595 - 606
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1172 KB) |  | HTML iconHTML  

    Wideband electromagnetic fields scattered from N distinct target-sensor orientations are employed for classification of airborne targets. Each of the scattered waveforms is parsed via physics-based matching pursuits, yielding N feature vectors. The feature vectors are submitted to a hidden Markov model (HMM), each state of which is characterized by a set of target-sensor orientations over which the associated feature vectors are relatively stationary. The N feature vectors extracted from the multiaspect scattering data implicitly sample N states of the target (some states may be sampled more than once), with the state sequence modeled statistically as a Markov process, resulting in an HMM due to the “hidden” or unknown target orientation. In the work presented here, the state-dependent probability of observing a given feature vector is modeled via physics-motivated linear distributions, in lieu of the traditional Gaussian mixtures applied in classical HMMs. Further, we develop a scheme that yields autonomous definitions for the aspect-dependent HMM states. The paradigm is applied to synthetic scattering data for two simple targets View full abstract»

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  • Passive ranging of a low observable ballistic missile in a gravitational field

    Page(s): 481 - 494
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1292 KB) |  | HTML iconHTML  

    In this paper we present an estimation algorithm for tracking the motion of a low-observable target in a gravitational field, for example, an incoming ballistic missile (BM), using angle-only measurements. The measurements, which are obtained from a single stationary sensor, are available only for a short time. Also, the low target detection probability and high false alarm density present a difficult low-observable environment. The algorithm uses the probabilistic data association (PDA) algorithm in conjunction with maximum likelihood (ML) estimation to handle the false alarms and the less-than-unity target detection probability. The Cramer-Rao lower bound (CRLB) in clutter, which quantifies the best achievable estimator accuracy for this problem in the presence of false alarms and nonunity detection probability, is also presented. The proposed estimator is shown to be efficient, that is, it meets the CRLB, even for low-observable fluctuating targets with 6 dB average signal-to-noise ratio (SNR). For a BM in free flight with 0.6 single-scan detection probability, one can achieve a track detection probability of 0.99 with a negligible probability of false track acceptance View full abstract»

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  • High resolution 3D “snapshot” ISAR imaging and feature extraction

    Page(s): 630 - 642
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1004 KB) |  | HTML iconHTML  

    We have developed a new formulation for three dimensional (3D) radar imaging of inverse synthetic aperture radar (ISAR) data based on recent developments in high resolution spectral estimation theory. Typically for non real-time applications, image formation is a two step process consisting of motion determination and image generation. The technique presented focuses on this latter process, and assumes the motion of the target is known. The new technique offers several advantages over conventional techniques which are based on the correlation imaging function. In particular, the technique provides for a direct 3D estimate (versus back projection to a 3D target grid matrix) of the locations of the dominant scattering centers using only a minimum set of independent 2D range-Doppler ISAR “snapshots” of the target. Because of the snapshot nature of the technique, it is particularly applicable to 3D imaging of sectors of sparse-angle data, for which the sidelobes of the correlation imaging integral become high. Furthermore, the technique provides for an estimate of amplitude and phase of each scattering center as a function of aspect angle to the target, for those aspect angles which encompass the set of 2D range-Doppler snapshots. Results illustrating the technique developed are presented for both simulated and static range data View full abstract»

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  • Airborne GMTI radar position bias estimation using static-rotator targets of opportunity

    Page(s): 695 - 699
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (364 KB) |  | HTML iconHTML  

    In target tracking systems: using GMTI (ground moving target indicator) radars on airborne platforms, the locations of these platforms are available from GPS-based estimates. However, these estimated locations are subject to errors that are, typically, stationary autocorrelated random processes, i.e., slowly varying biases. In situations where there are no known-location targets to estimate these biases, the next best recourse is to use targets of opportunity at fixed but unknown locations. Such targets can be, e.g., static rotators (ground-based radars with rotating antenna), which yield detections in moving target indicator (MTI) radars. It is shown that these biases can be estimated in such a scenario, i.e., they meet the complete observability condition. Following this, the achievable accuracy for a generic scenario is evaluated. It is shown that accurate georegistration can be obtained even with a small number of measurements View full abstract»

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  • Efficient multisensor fusion using multidimensional data association

    Page(s): 386 - 400
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1324 KB) |  | HTML iconHTML  

    We present the development of a multisensor fusion algorithm using multidimensional data association for multitarget tracking. The work is motivated by a large scale surveillance problem, where observations from multiple asynchronous sensors with time-varying sampling intervals (electronically scanned array (ESA) radars) are used for centralized fusion. The combination of multisensor fusion with multidimensional assignment is done so as to maximize the “time-depth” in addition to “sensor-width” for the number S of lists handled by the assignment algorithm. The standard procedure, which associates measurements from the most recently arrived S-1 frames to established tracks, can have, in the case of S sensors, a time-depth of zero. A new technique, which guarantees maximum effectiveness for an S-dimensional data association (S⩾3), i.e., maximum time-depth (S-1) for each sensor without sacrificing the fusion across sensors, is presented. Using a sliding window technique (of length S), the estimates are updated after each frame of measurements. The algorithm provides a systematic approach to automatic track formation, maintenance, and termination for multitarget tracking using multisensor fusion with multidimensional assignment for data association. Estimation results are presented for simulated data for a large scale air-to-ground target tracking problem View full abstract»

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  • Improved Kalman filter design for three-dimensional radar tracking

    Page(s): 727 - 739
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (932 KB) |  | HTML iconHTML  

    The problem of three-dimensional (3D) radar tracking is considered. The usual tracking filter design relying on first-order (or linear) approximations leads to poor convergence and erratic filter behavior in highly nonlinear situations. Simple filter algorithms that can overcome these ill effects are developed for two different types of 3D radar measurement. For each type of radar measurement, an accurate expression for the measurement covariance is obtained by evaluating inherent nonlinearities of radar measurements via coordinate transformation. Then algebraic manipulations and reasonable approximations are employed to yield a simple filter formulation based on the expression. The resulting filter equations are similar to the extended Kalman filter (EKF) and provide some useful insights into the behavior of linearized Kalman filters designed with radar measurements. Finally, simulation results show that the proposed approach is very effective in accounting for the measurement nonlinearities View full abstract»

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  • Passive polarimetric IR target classification

    Page(s): 740 - 751
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1400 KB) |  | HTML iconHTML  

    Automatic detection and recognition of targets by means of passive IR sensors suffer from limitations due to lack of sufficient contrast between the targets and, their backgrounds and among the facets of a target. A set of novel algorithms is designed and tested that uses the target and background Stokes parameters for detection, segmentation, and classification of targets, In these algorithms, it is assumed that for each pixel in the image data three of the four Stokes parameters are provided. This assumption is justified because we have developed a custom designed Polarimetric IR (PIR) imaging sensor that generates three of the Stokes parameters at each pixel location, in real-time. The empirical performance of the above algorithms, in terms of the probabilities of detection, false alarm rate, segmentation accuracy, and recognition probabilities are computed. The comparison of these results with the results associated with intensity-only imaging sensor (nonpolarimetric IR sensory data) shows that use of polarimetric information can noticeably improve the performance View full abstract»

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  • Surface movement radar data processing methods for airport surveillance

    Page(s): 563 - 585
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2076 KB) |  | HTML iconHTML  

    An airport surveillance function operating on surface movement radar (SMR) images is proposed and evaluated. The main contributions presented are the statistical error models of the target centroid and attributes extracted from radar images, developed and applied to the design of its main data processing blocks. Besides a multihypothesis image-to-tracks assignment method, a tracking filter using the extracted orientation and a classification scheme based on target attributes is detailed. The error models confidence and processing methods performance are demonstrated through simulation in representative scenarios View full abstract»

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  • Improved SAR target detection via extended fractal features

    Page(s): 436 - 451
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2112 KB) |  | HTML iconHTML  

    The utility of the extended fractal (EF) feature is evaluated for the enhancement of the focus of attention (FOA) stage of a synthetic aperture radar (SAR) automatic target recognition (ATR) system. Unlike more traditional SAR detection features that distinguish target pixels from the background only on the basis of contrast, the EF feature is sensitive to both the contrast and size of objects. Furthermore, the structure for the EF feature computational algorithm lends itself to very fast implementation, and it can be shown that the new feature has a CFAR-like (constant false alarm rate) property. We demonstrate the improved performance using the new feature by testing a number of different detection approaches over two databases of SAR imagery View full abstract»

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  • Identification of large aircraft

    Page(s): 706 - 710
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (412 KB) |  | HTML iconHTML  

    Large commercial aircraft are much more easily identified by radar than are fighter aircraft, because the former's two-dimensional images have sufficient details to let one recognize the aircraft's shape. The usual problem with identification based on shape is lack of knowledge of the aspect angle. As an indication of the relative ease with which commercial aircraft can be identified, this note describes a shape-based identification method that does not require knowledge of the aspect angle 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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Editor-in-Chief
Lance Kaplan
Army Research Laboratory