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检索条件"任意字段=Conference on Signal and Data Processing of Small Targets 1999"

共 764 条记录，以下是71-80 订阅

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AOA estimation with merged measurements from squint beam monopulse data in conjunction with multiple range samples

AOA estimation with merged measurements from squint beam mon...

引用

conference on signal and data processing of small targets

作者： Brown, GC Blair, WD Ogle, TL GTRI SEAL AMDD Atlanta GA 30332 USA

ISBN: (纸本)0819450774

A key assumption in monopulse based angle-of-arrival (AOA) estimators is that at most one return from a single object is present in each range cell, or equivalently in each sample of the matched filter output. These algorithms break down if the data consists of merged measurements-multiple target returns contained in the same range cell. The proposed technique makes use of data from a three channel monopulse radar to estimate the AOA of two targets from merged measurements. Specifically, the technique capitalizes on the structure of squint beams in conjunction with multiple range samples to resolve the multiple targets. The paper focuses on the development of the new algorithm along with results from computer simulations that demonstrate its viability. To illustrate the utility of this technique to target tracking problems, comparative Monte Carlo results of performance of a tracker with the new technique and conventional monopulse AOA estimates are provided.

关键词： merged measurements monopulse angle of arrival radar signal processing

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TRACKING WITH FUSED NONCOINCIDENT MEASUREMENTS

TRACKING WITH FUSED NONCOINCIDENT MEASUREMENTS

引用

conference on signal and data processing of small targets 1994

作者： RAGO, C WILLETT, P BARSHALOM, Y UNIV CONNECTICUT STORRSCT 06269

ISBN: (纸本)0819415391

If members of a suite of sensors from which fusion is to be carried out are not co-located, it is unreasonable to assume that they share a common resolution cell grid; this is generally ignored in the data fusion community. In this paper we explore the effects of such `noncoincidence', and we find that what at first seems to be a problem can in fact be exploited. The idea is that a target is known to be confined to an intersection of overlapping resolution cells, and this overlap is generally small.

关键词： Sensors Radar Error analysis Stochastic processes data fusion Filtering (signal processing) Monte Carlo methods Target detection Optical resolution Sensor fusion

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GMTI-tracking and information fusion for ground surveillance

GMTI-tracking and information fusion for ground surveillance

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13th conference on signal and data processing of small targets

作者： Koch, WG FKIE FGAN D-53343 Wachtberg Germany

ISBN: (纸本)0819441872

The aim of ground surveillance with airborne GMTI radar is the near real-time production of a dynamic ground picture. Since the sensors often record merely certain aspects of the situation of interest, information fusion is of particular importance. In addition, even after platform motion compensation by signal processing techniques (STAP), ground moving targets can well be masked by the clutter notch of the sensor. This physical phenomenon directly results from the low-DOPPLER characteristics of the targets and causes interfering fading effects that seriously affect the tracking performance/continuity. In this context a GMTI sensor model provides significant performance improvements being relevant also to sensor data fusion. The Minimum Detectable Velocity (MDV) proves to be an important sensor parameter explicitly entering into GMTI tracking. In combination with road map information or sensor data fusion the refined model can in particular alleviate the recognition of stopping targets. A numerical example quantitatively illustrates the potential gain by exploiting GMTI-modeling, road-maps, and sensor fusion.

关键词： ground moving targets (GMT) GMTI radar Bayesian target tracking PDA MHT sensor data fusion road map information minimum detectable velocity (MDV) space-time adaptive processing (STAP) doppler blindness

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THE APPLICATION OF DIFFERENCE METHOD TO DIM POINT TARGET DETECTION IN INFRARED IMAGES

THE APPLICATION OF DIFFERENCE METHOD TO DIM POINT TARGET DET...

引用

conference on signal and data processing of small targets 1994

作者： YANG, WP SHEN, ZK LI, ZY NATL UNIV DEF TECH DEPT ELEC ENGHUNAN 410073PEOPLES R CHINA

ISBN: (纸本)0819415391

This paper deals with the detection of dim point targets in infrared images. Dim point targets detection is always a difficulty in information processing. Researchers have proposed many effective methods in this aspect, here this paper no longer mentions them but will introduce a new method. Whereas difference method has obtained good result in one dimensional signal processing this paper manages to apply it to two dimensional signal processing, that is to say, dim point targets detection in infrared images of low SNR. The image background is color noise, and its column correlation is strong. So, ordinary methods probably lose the true targets because of the strong color noise, but unlike them, difference method can overcome this shortcoming, it can eliminate correlation noise and enhance useful information, finally pick out the probable targets from noise background. In the paper, the method was given a more extensive acount. In order to improve the detection effect, we utilized prefilter, The prefilter is realized by the alpha filter. Because the same targets have same location in more than three frames, using alpha filter can utilize the information of adjacent frames, increase the SNR of the raw data and reduce the noise of the images. © 1994 SPIE. All rights reserved.

关键词： signal to noise ratio

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SPATIAL signal-processing FOR INFRARED DETECTION

SPATIAL SIGNAL-PROCESSING FOR INFRARED DETECTION

引用

conference on signal and data processing of small targets 1994

作者： REISS, DB MIT LINCOLN LABLEXINGTONMA 02173

ISBN: (纸本)0819415391

We conduct a comparative study of the performance of a variety of spatial filtering techniques for detecting small targets against infrared terrain backgrounds. We consider parametric and nonparametric filters as well as an example of a robust estimation technique as applied to a parametric filter. In addition, we consider the effects of a clustering algorithm on filtering performance. Some of the filtering algorithms that we consider are matched filters, Laplacian filters, quadratic filters and the Robinson filter. Several filter dimensions are considered as well as the effects of a guard band. These algorithms are tested against the Lincoln Laboratory Infrared Measurement Sensor database which is comprised of high resolution dual band (3.5 to 5.2 (mu) , and 8 to 12 (mu) ) data taken at a variety of sites under a broad spectrum of atmospheric conditions and times of day. Target insertion effects are modeled carefully, incorporating the straddling of targets across adjacent pixels as well as the effects of diffractive blurring. We find that many of the filters that we have tested show similar performance and all are clutter limited.

关键词： Digital filtering Filtering (signal processing) Sensors Target detection Detection and tracking algorithms Mid-IR Linear filtering Nonlinear filtering Long wavelength infrared Infrared radiation

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Multiframe detection of direction of moving targets

Multiframe detection of direction of moving targets

引用

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

引用

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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Multitarget detection and acquisition: A unified approach

Multitarget detection and acquisition: A unified approach

引用

conference on signal and data processing of small targets 1999

作者： Mahler, R O'Hely, M Lockheed Martin Tact Def Syst Eagan MN USA

ISBN: (纸本)0819432954

Suppose that a multitarget tracker is used to track a dim target in heavy clutter. In the paper "Characteristics of the Acquisition of a Dim Target in Clutter," Oliver Drummond has pointed out that, for such a tracker, target acquisition (i.e., determining whether or not a target is present in a sensor Field of View corrupted by persistent clutter tracks) is a very different problem than target detection (i.e., determining whether or not a target is present in a pixel corrupted by noise). In particular, target acquisition requires two Receiver Operating Characteristic (ROC) curves;whereas target target detection requires only one. In past presentations at this and other conferences and in the book Mathematics of data Fusion, we have introduced "finite-set statistics (FISST)", a direct generalization of conventional single-sensor, single-target statistics to the multitarget realm. In this paper we show how FISST results in a unification of both detection and acquisition under a familiar decision-theoretic framework. The basic idea is to use a unified Bayesian single-target tracker with clutter models, rather than a multitarget tracker. In analogy to a conventional detection problem (i.e., deciding between the hypotheses "noise only" versus "target + noise"), the acquisition problem is reduced to a conventional decision problem (i.e., deciding between the hypotheses "clutter only" versus "target + clutter"). In particular, we show how to define an "acquisition ROC curve" for this sort of generalized detection problem.

关键词： data fusion multitarget tracking detection acquisition random sets

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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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