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conference on signal and data processing of small targets 1997

作者： Lampropoulos, GA Boulter, JF A.U.G. Signals Ltd. (Canada) Defence Research Establishment Valcartier (Canada)

ISBN: (纸本)0819425850

In this paper we present a new technique for the estimation of the velocity of moving targets using sequential frames. This estimation process may be used to estimate a potential set of velocities of moving targets which in turn may be used by three-dimensional (3-D) directional matched filters. It may also be used as a target trajectory estimation technique. The method is based on a local probability density matching segmentation technique with spatiotemporal associations. Experimental results are presented.

关键词： moving target indicator spatiotemporal trajectory estimation spatiotemporal velocity estimation

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Target selection using a utility theoretic approach

Target selection using a utility theoretic approach

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13th conference on signal and data processing of small targets

作者： Özener, MS Yardimci, Y Orta Dogu Teknik Univ Enformat Ensitusu TR-06351 Ankara Turkey

ISBN: (纸本)0819441872

Modern target tracking systems perform different tasks among which are target detection, selection and tracking. in this study, we describe a target selection technique based on Utility Theory. The utility of each target is assumed to be a linear combination of some basis functions that act on certain features of the target such as size, intensity, speed and direction. The unknown parameters of the basis functions and their weights are selected using a descent type optimization technique. Simulation results are presented.

关键词： Target detection Cameras Automatic tracking data processing Infrared imaging Infrared radiation MATLAB Neural networks Sensors signal processing

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The PMHT for maneuvering targets

The PMHT for maneuvering targets

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conference on signal and data processing of small targets

作者： Willett, P Ruan, Y Streit, R Univ Connecticut Storrs CT 06269 USA

ISBN: (纸本)0819428221

The Probabilistic Multi-Hypothesis Tracker (PMHT) of Streit and Luginbuhl(1) uses the EM algorithm and a slight modification of the usual target-tracking assumptions to combine data-association and filtering. The performance of the PMHT to date has been comparable to that of existing tracking algorithms;however, part of its appeal is a consistent and extensible statistical foundation, and it is the extension to the tracking of maneuvering targets which we explore in this paper. The basis, as with many algorithms designed for maneuvering targets, is of an underlying and hidden "model-switch" process controlled by a Markov probability structure. Performance of the modified PMHT is investigated both for maneuvering and non-maneuvering targets. The improved performance observed in the latter case is somewhat surprising.

关键词： target tracking multiple models EM algorithm

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Use of joint data association probabilities for covariance consistency

Use of joint data association probabilities for covariance c...

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13th conference on signal and data processing of small targets

作者： Blair, WD Brown, GC Georgia Inst Technol Georgia Tech Res Inst Atlanta GA 30332 USA

ISBN: (纸本)0819441872

Covariance consistency is a critical element of a robust target tracking system. Target maneuvers and measurement origin uncertainty pose significant challenges to a tracking algorithm achieving covariance consistency. The Interacting Multiple Model (IMM) estimator is a nearly consistent estimator for tracking maneuvering targets. While the Probabilistic data Association Filter (PDAF) achieves covariance, consistency for a single target in presence of false alarms, achieving covariance consistency while tracking multiple closely-spaced targets is an open Issue. When using an unique assignment technique for associating measurements-to-tracks, the measurements are typically processed with the track filter as if the measurement-to-track association probabilities are unity for each measurement-track pair. This processing of the measurements results in poor covariance consistency for closely-spaced targets. In this paper, the use of approximate association probabilities for each measurement-to-track pair is proposed for the unique assignments and included in the track filter processing of the measurement to enhance the covariance consistency for closely-spaced targets.

关键词： tracking data association radar systems

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Detection and localization of multiple unresolved extended objects via monopulse radar signal processing

Detection and localization of multiple unresolved extended o...

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17th conference on signal and data processing of small targets

作者： Zhang, X Willett, P Bax-Shalom, Y Univ Connecticut Dept Elect & Comp Engn Storrs CT 06269 USA

ISBN: (纸本)0819459186

With high resolution radars, realistic objects should be considered as extended rather than point targets. If several closely-spaced targets fall within the same radar beam and between adjacent matched filter samples in range, the full monopulse information from all of these samples can and should be used for estimation, both of angle and of range (with the range to sub-bin accuracy). To detect and localize multiple unresolved extended targets, we establish a model for monopulse radar returns from extended objects, and use a maximum likelihood estimator to localize the targets. Rissanen's minimum description length (MDL) will be used to decide the number of existing extended objects. We compare the new extended target monopulse processing scheme with previously developed point target monopulse techniques to show the improvement in terms of the estimation of target locations, the detection of the number of existing targets, and the tracking performance with a multiple hypothesis tracker (MHT) using the output from the proposed extended target monopulse processor.

关键词： monopulse radar extended target unresolved target tracking

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LOW signal-TO-CLUTTER RATIO processing OF RADAR signalS

LOW SIGNAL-TO-CLUTTER RATIO PROCESSING OF RADAR SIGNALS

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conference on signal and data processing of small targets 1994

作者： CHAKRAVARTHI, PR WEINER, DD JET PROP LAB PASADENACA 91109

ISBN: (纸本)0819415391

In radar problems involving weak signal detection conventional space-time processing cannot be used to separate the target from the clutter when the spatial and Doppler spectra of the target and clutter overlap. In such problems the concept of the locally optimum detector (LOD) is useful in coming up with a decision rule to discriminate between the two hypotheses of signal present or signal absent. The clutter, which may be correlated, can arise from either a non-Gaussian or Gaussian random process. For correlated multivariate K-distributed clutter it is shown in this paper that performance improvements can be obtained with an LOD receiver compared to the conventional Gaussian linear receiver.

关键词： signal detection Sensors signal processing Radar Receivers Radar signal processing Monte Carlo methods Bessel functions signal to noise ratio Statistical analysis

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Cramer-Rao bound on image registration accuracy

Cramer-Rao bound on image registration accuracy

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conference on signal and data processing of small targets 1997

作者： Auerbach, SP Hauser, LE Science Applications International Corp. (United States)

ISBN: (纸本)0819425850

Precision registration (alignment) of images is utilized in dim target detection, temporal change detection, and other surveillance applications. The Cramer-Rao bound on the accuracy of parameter estimation governs the fundamental limit on the accuracy of image registration. This presentation derives the Cramer-Rao bound on registration accuracy, with emphasis on how registration accuracy depends on sensor noise, scene geometry, image characteristics and the number of pixels used in the registration process, and compares the Cramer-Rao bound prediction to registration results from the SAIC IR processing code, STAS, for both synthetically generated scenes and real IR data.

关键词： image processing Cramer-Rao bound registration signal processing

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Maritime small targets Detection Method for Passive Bistatic Radar Using Non-Cooperative Radar as Illuminator of Opportunity

Maritime Small Targets Detection Method for Passive Bistatic...

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2019 IEEE International conference on signal, Information and data processing, ICSIDP 2019

作者： Jie, Song Guoqing, Wang Caisheng, Zhang Research Institute of Information Naval Aviation University YanTai China

ISBN: (纸本)9781728123455

This paper proposes the maritime small targets detection method of passive bistatic radar (PBR) using a noncooperative pulse radar as an illuminator. Compared with other opportunity illuminators, the transmitting signal of a radar usually has a better ambiguity function, which leads to a higher range resolution, but there is a problem that radar transmitting signal parameters are unknown, and radar signal processing, such as pulse compression, non-coherent integration, and CFAR processing cannot be conducted accurately. The proposed method estimates radar signal parameters from the direct-path signal, and uses estimated parameters to radar signal processing of the scattered echo. The experiments use the shore-based maritime surveillance radar as a transmitter and ships in the harbor as the targets, which show that the proposed method can be applied to maritime small targets detection successfully. © 2019 IEEE.

关键词： Radar signal processing

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Sonar recognition of targets embedded in sediment

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NEURAL NETWORKS 1995年第7-8期8卷 1263-1273页

作者： Roitblat, HL Au, WWL Nachtigall, PE Shizumura, R Moons, G ORINCON CORP SAN DIEGO CA USA

Dolphins have biological sonar abilities that exceed those of any man-made system in an aquatic environment. One problem of particular importance, and for which only limited capabilities exist, is the detection and recognition of targets buried under sediment. This paper reviews dolphin echolocation capabilities and describes a system that uses a dolphin-like signal and biomimetic signal processing mechanisms to emulate the performance of the dolphin on such targets. The system employed a digitized dolphin click with a center frequency of 120 kHz and a 3dB bandwidth of 39 kHz, 50 mu s duration. This signal was transmitted through seawater into mud and the echoes reflected from the objects were recorded and digitized. Two spectral estimators were used to extract a time-frequency representation of the echo. One was based on short-time fast Fourier transforms, and the other was based on an autoregressive estimator. The time-frequency representation was then processed by a separate backpropagation neural network for each estimator, designed to derive independent identifications of the targets. These identifications were then combined in a modified probabilistic neural network that used a linear transfer function rather than a binary function for its output. Finally the output of the probabilistic network was processed symbolically by a simple expert system. Three experiments are described in which the system was used to discriminate a small stainless-steel cylinder from cylinders of the same size made of hollow aluminium, foam-filled aluminium, or coral rock embedded in resin. Each of the targets was presented buried in mud at a depth of several centimeters. The system proved highly effectively at recognizing these buried targets.

关键词： dolphins echolocation sonar backpropagation probabilistic neural networks data fusion

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MWIRSTD: A MWIR small TARGET DETECTION dataSET 31

MWIRSTD: A MWIR SMALL TARGET DETECTION DATASET

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2024 International conference on Image processing

作者： Kumar, Nikhil Upadhyay, Avinash Sharma, Shreya Sharma, Manoj Singh, Pravendra IIT Roorkee Roorkee Uttar Pradesh India Bennett Univ Greater Noida Uttar Pradesh India Visual Cognit Lab Pvt Ltd Noida Uttar Pradesh India

ISBN: (纸本)9798350349405;9798350349399

This paper presents a novel mid-wave infrared (MWIR) small target detection dataset (MWIRSTD) comprising 14 video sequences containing approximately 1053 images with annotated targets of three distinct classes of small objects. Captured using cooled MWIR imagers, the dataset offers a unique opportunity for researchers to develop and evaluate state-of-the-art methods for small object detection in realistic MWIR scenes. Unlike existing datasets, which primarily consist of uncooled thermal images or synthetic data with targets super-imposed onto the background or vice versa, MWIRSTD provides authentic MWIR data with diverse targets and environments. Extensive experiments on various traditional methods and deep learning-based techniques for small target detection are performed on the proposed dataset, providing valuable insights into their efficacy. The dataset and code are available at https://***/avinres/MWIRSTD.

关键词： small target detection small and dim target detection point target detection MWIR dataset defence application

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