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检索条件"任意字段=13th Conference on Signal and Data Processing of Small Targets"

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the method of range profile for step frequency MMW radar based on wavelet transform power spectrum estimator

The method of range profile for step frequency MMW radar bas...

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13th conference on signal and data processing of small targets

作者： Li, YH Gao, DT Shen, QH Li, XG Nanjing Univ Dept Elect Sci & Technol Nanjing 210093 Peoples R China

ISBN: (纸本)0819441872

the method of range profile for step frequency MMW radar targets based on wavelet transform power spectrum estimator is studied. We show how the Fourier power spectrum can be detected by using the wavelet function coefficients (WFC) of the DWT. this method can successfully measure the power spectrum in samples for which traditional methods often fail because the sample are finite sized, have a complex geometry, or are varyingly sampled. We demonstrate that the spectrum features, such as the power law index, the magnitude, and the typical scales can be determined by the DWT reconstructed spectrum. We apply this method to the practical step frequency MMW radar target echo signals, and on the condition of the same sampling frequency and sampling data length, it can achieve one dimensional range profile with profile's resolution superior to FFT's, so the one dimensional range profile of targets can be analyzed with high resolution, the detail algorithm of range profiles spectrum estimation based on wavelet transforming multirange cells is proposed. Compare with FFT algorithm, using wavelet spectrum estimator of short data series, we can achieves high resolution, high accuracy, and low SNR threshold. the Experiment results make clear that the DWT estimator is a sensitive tool in range profile of step frequency MMW radar.

关键词： wavelet transform multiresolution analysis spectrum estimator radar signal image processing

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the target profile identification of step frequency MMW radar based on wavelet neural network

The target profile identification of step frequency MMW rada...

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13th conference on signal and data processing of small targets

作者： Li, YH Gao, DT Shen, QH Li, XG Nanjing Univ Dept Elect Sci & Technol Nanjing 210093 Peoples R China

ISBN: (纸本)0819441872

With the increased availability of coherent wide band radar, there has been a renewed interest in the target recognition of MMW frequency step radar. A large bandwidth gives high resolution in range which means target recognition may be possible. In this paper, by integrating wavelet with neural network, a new adaptive wavelet function neural network is proposed. An artificial neural network with wavelet as weight coefficients is developed for pattern recognition. It is inspired by wavelet transform theory and feed forward neural network. the good localization characteristics of wavelet functions in both time and frequency space allow hierarchical multi-resolution learning of input-output data mapping. the wavelet shapes are adaptively computed to minimize an energy function for a specific application of radar targets. the mathematical frame of the neural network is introduced and error back propagation algorithm is used. the procedure of using wavelet neural network for identification is described in detail. Based on the target specific information offered by the range profiles of step frequency MMW radar targets, the wavelet neural network is applied to recognition of three kinds of practical radar targets. We find that we can reliably distinguish for three targets over a range of aspect angle. Experiment results indicate that the new feature vector in low dimension is valuable for target recognition, the wavelet neural network has faster convergence speed and higher correct recognition rate and the noise resistance character is good.

关键词： wavelet neural network multi-resolution analysis target identification radar signal image processing

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the evidential reasoning tracker: Further steps towards a unified theory of sensor fusion

The evidential reasoning tracker: Further steps towards a un...

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13th conference on signal and data processing of small targets

作者： Mahalanabis, A Lobbia, RN Nguyen, QB Boeing Co Boeing Phantom Works Div Seattle WA 98124 USA

ISBN: (纸本)0819441872

the discipline of Sensor and data Fusion is increasingly characterized by a set of disparate tools and principles. An initial consideration of these principles belies any theoretical coherence or commonality. Yet secondary inspection may begin to reveal a fundamental basis that ties together these algorithms. this paper represents the second in a multi-part discussion that attempts to explore this common basis. In particular, while our first discussion centered around the use of a traditional state estimation technique (Kalman Filtering) to perform decision-level identity fusion, in the paper we take the opposite approach, using a traditional decision-level ID technique (Dempster-Shafer Calculus) to do state estimation.

关键词： Sensor data fusion

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small moving object detection using adaptive subband decomposition and fractional lower order statistics in video sequences

Small moving object detection using adaptive subband decompo...

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13th conference on signal and data processing of small targets

作者： Bagci, AM Yardimci, Y Çetin, AE Bilkent Univ Dept Elect & Elect Engn Ankara Turkey

ISBN: (纸本)0819441872

In this paper, a small moving object method detection method in video sequences is described. In the first step, the camera motion is eliminated using motion compensation. An adaptive subband decomposition structure is then used to analyze the motion compensated image. In the highband subimages moving objects appear as outliers and they are detected using a statistical detection test based on lower order statistics. It turns out that in general, the distribution of the residual error image pixels is almost Gaussian. On the other hand, the distribution of the pixels in the residual image deviates from Gaussianity in the existence of outliers. By detecting the regions containing outliers the boundaries of the moving objects are estimated. Simulation examples are presented.

关键词： moving object detection adaptive subband decomposition wavelet transform lower order statistics

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Detection of small periodic binary signals in image sequences: Moving signal sources

Detection of small periodic binary signals in image sequence...

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13th conference on signal and data processing of small targets

作者： Feldman, G Bar, D Tugendhaft, I Soreq Nucl Res Ctr IL-81800 Yavne Israel

ISBN: (纸本)0819441872

An algorithm developed for detection, localization and tracking of periodic signals, that appear as few-pixel blobs in image sequences and have a characteristic binary pattern in the temporal domain, is described. It is the further development of our original algorithin (1) that extends its capabilities to the detection of moving targets and also improves its performance in some cases. We sketch those stages of the algorithm that were already described and discussed in (1). then we describe in full detail the new features of our algorithm, namely: 1) A search for signal sources that move with a relatively-slowly-varying velocity. this velocity is adaptively estimated and re-estimated in order to maximize the correlation with the time-domain pattern. While the first estimate is performed at pixel level, the re-estimation ( when tracking detected signals) is performed at the blob level. 2) Re-estimation of the spatial domain background around the already-detected blob, yielding a more precise estimate of the blob. the new algorithm was tested by processing simulated, as well as real, image sequences. the results are discussed. the principal conclusion is that all good features of our original algorithm, namely: efficient detection of visible signals, reasonable detection of invisible signals, insensitivity to local motions in a video, to camera motion, to intensity changes and to any weak flickering of background, remain valid. However, we are required to increase slightly the minimal length of the time-domain correlation (thus, the delay in detection) at the same false alarm probability. Finally, we also consider the problem of the most suitable temporal-domain pattern for signals to be detected.

关键词： image sequence signal detection image registration pattern background subtraction correlation

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Stereo vision for small targets in IR image sequences

Stereo vision for small targets in IR image sequences

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13th conference on signal and data processing of small targets

作者： Jutzi, B Gabler, R Jaeger, K FGAN FOM Res Inst Optron & Pattern Recognit D-76275 Ettlingen Germany

ISBN: (纸本)0819441872

Surveillance systems against missile attacks require the automatic detection of targets with low false alarm rate (FAR). Infrared Search and Track (IRST) systems offer a passive detection of threats at long ranges. For maximum reaction time and the arrangement of counter measurements, it is necessary to declare the objects as early as possible. For this purpose the detection and tracking algorithms have to deal with point objects. Conventional object features like shape, size and texture are usually unreliable for small objects. More reliable features of point objects are three-dimensional spatial position and velocity. At least two sensors observing the same scene are required for multi-ocular stereo vision. Mainly three steps are relevant for successful stereo image processing. First of all the precise camera calibration (estimating the intrinsic and extrinsic parameters) is necessary to satisfy the demand of high degree of accuracy, especially for long range targets. Secondly the correspondence problem for the detected objects must be solved. thirdly the three-dimensional location of the potential target has to be determined by projective transformation. For an evaluation a measurement campaign to capture image data was carried out with real targets using two identical IR cameras and additionally synthetic IR image sequences have been generated and processed. In this paper a straightforward solution for stereo analysis based on stationary bin-ocular sensors is presented, the current results are shown and suggestions for future work are given.

关键词： IRST infrared stereo multiple target tracking point targets image sequence processing false alarms camera calibration projective reconstruction

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A comparison of recursive angle-only target tracking algorithms

A comparison of recursive angle-only target tracking algorit...

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13th conference on signal and data processing of small targets

作者： Elliott, RJ Dufour, F Malcolm, WP Univ Calgary Fac Management Calgary AB T2N 1N4 Canada

ISBN: (纸本)0819441872

In this article we consider estimation for a discrete-time hybrid dynamical system. Hybrid dynamical systems arise quite naturally in many estimation problems, for example target tracking in a maneuvering target scenario. the most commonly used suboptimal estimation algorithm for the problem class just described, is the so called Interacting Multiple Model (IMM) algorithm. In the work presented here, angle-only target tracking problems are considered, in particular we consider scenarios including maneuvering targets. One approach to this class of problem is to apply the IMM scheme. Using the scheme in Elliott and Dufour,(1) we compute estimates of position and velocity for a maneuvering target when only the target bearing is available. these estimates are compared to the IMM scheme applied to the same problem. It is shown that the algorithm proposed in Elliott and Dufour(1) offers significant improvements over the IMM scheme.

关键词： angle-only tracking hybrid dynamics maneuvering targets reference probability

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3-D track initiation in clutter using 2-D measurements

3-D track initiation in clutter using 2-D measurements

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13th conference on signal and data processing of small targets

作者： Lin, L Kirubarajan, T Bar-Shalom, Y Univ Connecticut Dept ECE Storrs CT 06269 USA

ISBN: (纸本)0819441872

In this paper we present an algorithm for initiating 3-D tracks using range and azimuth (bearing) measurements from a 2-D radar on a moving platform. the work is motivated by the need to track possibly low-flying targets, e.g., cruise missiles, using reports from an aircraft-based surveillance radar. Previous work on this problem considered simple linear motion in a flat earth coordinate frame [13]. Our research extends this to a more realistic scenario where the earth's curvature is also considered. the target is assumed to be moving along a great circle at a constant altitude. After the necessary coordinate transformations, the measurements are nonlinear functions of the target state and the observability of target altitude is severely limited. the observability, quantified by the Cramer-Rao Lower Bound (CRLB), is very sensitive to the sensor-to-target geometry. the paper presents a Maximum Likelihood (ML) estimator for estimating the target motion parameters in the Earth Centered Earth Fixed coordinate frame from 2-D range and angle measurements. In order to handle the possibility of false measurements and missed detections, which was not considered in [13], we use the Probabilistic data Association (PDA) algorithm to weight the detections in a frame. the PDA-based modified global likelihood is optimized using a numerical search. the accuracies obtained by the resulting ML-PDA estimator are quantified using the CRLB for different scnsor-target configurations. It is shown that the proposed estimator is efficient, that is, it meets the CRLB. Of particular interest is the achievable accuracy for estimating the target altitude, which is not observed directly by the 2-D radar, but can be only inferred from the range and bearing observations.

关键词： target tracking track initiation Cramer-Rao lower bound NIL estimator probabilistic data association

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Vulnerability of recent GPS adaptive antenna processing (and all STAP/SLC) to statistically non-stationary jammer threats

Vulnerability of recent GPS adaptive antenna processing (and...

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13th conference on signal and data processing of small targets

作者： Kerr, th TeK Associates Lexington MA USA

ISBN: (纸本)0819441872

We alert the reader here to an apparent vulnerabilily in recent adaptive antenna processing that claims increased GPS jammer resistance via use of lucrative new approaches to adaptive beamforming and/or will-steering but, unfortunately, presumes only simplistic unsophisticated wideband barrage WGN jammers as threats. When jammers, are less cooperative by being statistically non-stationary (e.g., by exhibiting time-varying means or biases, by being synchronized blinking jammer pairs, or by varying the total power output with time), then statistics oil the jammers can apparently no longer be successfully extracted from the time-averages (even in post-processing mode using long blocks of received data that was saved) because ergodicity of the underlying intermediate covariance estimate is lost. this unpleasant situation arises or exists for abstracted, idealized STAP or SLC algorithms making use of the, by now, familiar fundamental STAP-related equation: R-v(-1), where this necessary intermediate covariance estimate R = R-1 + R-2 + R-3 has the three indicated constituent components due to thermal/environmental noise, clutter, and jammers, respectively. Without an ability to accurately estimate R-3, the appropriate jammer nullings apparently can no longer be activated successfully. Such systems susceptible to jamming can be revealed by in-situ tests with simple equipment. Topics herein include updates to PRN generation, updates to statistical tests in general and to CLT in particular and all three updates being new to most engineers.

关键词： janlining threats from first st at istical principles 101 space time adaptive procossing vulnerabilities CPS vulnerability to jamming by non-stationary random signals side lobe cancelers pseudo-random noise generation update CLT update statistical tutorial

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Exact methodology for testing linear system software using idempotent matrices and other closed-form analytic results

Exact methodology for testing linear system software using i...

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13th conference on signal and data processing of small targets

作者： Kerr, th TeK Associates Lexington MA USA

ISBN: (纸本)0819441872

We alert the reader here to a variety of structural properties associated with idempotent matrices that make them extremely useful in the verification/validation testing of general purpose control and estimation related software. A rigorous general methodology is provided here along with its rationale to justify use of idempotent matrices in conjunction with other tests (for expedient full functional coverage) as the basis of a coherent general strategy of software validation for these particular types of applications. the techniques espoused here are universal and independent of the constructs of particular computer languages and were honed from years of experience in crosschecking Kalman filter implementations in several diverse commercial and military applications. While standard Kalman filter implementation equations were originally derived by Rudolf E. Kalman in 1960 using the Projection theorem in a Hilbert Space context (with prescribed inner product related to expectations), there are now comparable Kalman filter results for systems described by partial differential equations (e.g., arising in some approaches to image restoration or with some distributed sensor situations for environmental toxic effluent monitoring) involving a type of Riccati-like PDE equation to be solved for the estimation error. the natural framework for such infinite dimensional PDE formulations is within a Banach Space (being norm-based) and there are generalizations of idempotent matrices similar to those offered herein for these spaces as well that allow closed-form test solutions for infinite dimensional linear systems to verify and confirm proper PDE implementations in S/W code. Other closed-form test case extensions discussed earlier by the author have been specifically tailored for S/W verification of multichannel maximum entropy power spectral estimation algorithms and of approximate nonlinear estimation implementations of Extended Kalman filtering and for Batch Least Squares (B

关键词： verification & validation of linear system software sub-modules using analytic closed-form results ODE's and PDE's trade-off's in batch filter use revised assessment of preferred squareroot filter implementations

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