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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51-60 订阅

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MAXIMIZATION OF RADAR SCAN FRAME TIME FOR TRACKING A MANEUVERING TARGET

MAXIMIZATION OF RADAR SCAN FRAME TIME FOR TRACKING A MANEUVE...

引用

conference on signal and data processing of small targets 1994

作者： MALAKIAN, K MARTIN MARIETTA GOVT ELECTR SYST MOORESTOWNNJ 08057

Analytic expressions are derived based on tracker characteristics that determine the maximum scan frame time required to track a maneuvering target. The tracker characteristics chosen are: filter gain, measurement cor... 详细信息

ISBN: (纸本)0819415391

关键词： Radar Filtering (signal processing) Fourier transforms Electronic filtering Image filtering

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Does extra information always help in data fusion?

Does extra information always help in data fusion?

引用

conference on signal and data processing of small targets 1999

作者： Perrella, A Glover, C Waugh, S Inst Def Analyses Alexandria VA 22311 USA

ISBN: (纸本)0819432954

Adding new sensor metric information into a data fusion process does not always improve performance and can sometimes produce poorer results.(1.2) References 1 and 2 used examples to shaw that-in some instances and contrary to expectation-adding new information resulted in poorer rather than improved performance, even though the information itself was correct. Correct is being used here to describe data that may be in error because of sensor deficiencies (e.g., large random or bias errors in azimuth, elevation, or range) but whose error characteristics are accurately described and known to the fusion process. In other words, the fusion process is not being lied to by misrepresentation of the data quality. In this sense, an individual data point may be inaccurate, but the fusion process is capable of properly weighting that point in an optimal sense so that its statistical inaccuracy does not damage the final product any more than a data point from a better sensor that has less statistical inaccuracy. In a multiple-sensor fusion process, these kinds of results have been cited as reasons for not using data from poorer quality sensors for fear of diluting the performance of the better quality sensors. This paper explores the counterintuitive findings from these referenced examples and evaluates under what conditions lesser quality sensors or sensors that mistakenly overestimate their own data quality should be allowed to contribute to a sensor fusion process.

关键词： data fusion multiple-sensor fusion skeptical fusion

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Simulation of signal and data processing for a pair of GEO IR sensors

Simulation of signal and data processing for a pair of GEO I...

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19th conference on signal and data processing of small targets

作者： Keil, Karl-Heinz Hupfer, Werner EADS Astrium GmbH Bremen Germany

ISBN: (纸本)9780819468475

This paper describes experiences and results from developing a basic signal and data processing simulation for a pair of GEO IR sensors observing the boost phase of Theater Ballistic Missiles (TBM). The goal of such a system is the detection of launched TBM, also against a cloud background, and the tracking from cloud break ideally up to boost-end. Two GEO satellites are used for stereo view of one and the same non-global limited Field-of-Regard (FOR). They are positioned in such a way that both cover the FOR and provide a sufficient triangulation baseline. signal processing is applied for each of both passive IR sensors in order to detect and track the TBM on the focal plane. The applied approach can be summarized under the term 'velocity filtering'. data processing operates on the 2-D signal processing input from both IR sensors, i.e. azimuth and elevation line-of-sight (LOS) angles as well as their rates. The goal is to provide 3-D tracks of the targets, which can be used to cue early warning or fire control radars. The underlying simulation model constitutes a prototype and vehicle for further research. Nevertheless, even in its current stage it provides a first tool for the analysis and evaluation of corresponding sensor design concepts.

关键词： signal processing data processing Satellites Filtering (signal processing) Digital filtering Sensors Clouds Infrared sensors Target detection Optical filters

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Tracking with asynchronous multiple sensors

Tracking with asynchronous multiple sensors

引用

13th conference on signal and data processing of small targets

作者： Gray, JE McCabe, DH USN Ctr Surface Warfare Dahlgren Div Syst Res & Technol Dept Dahlgren VA 22448 USA

ISBN: (纸本)0819441872

Sensor data fusion has long been recognized as a means to improve target tracking. Common practice assumes that the sensors used are synchronous (i.e., perform the, same operation at the identical time), take measurements at the same time and have no communication delays between sensor platforms and the central processing center. Such assumptions are not valid in practice. This paper removes these assumptions when dealing with multisensor target tracking. In particular, it assumes that the sensors used can have different data rates and communication delays between local and central platforms. A new tracking algorithm using asynchronous sensors is proposed and derived in this paper.

关键词： Filtering (signal processing) Lithium Sensors Silicon Zinc Electronic filtering Lutetium data communications data processing signal processing

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COMPARISON OF POINT-SOURCE ALGORITHMS FOR OPTIMUM ACQUISITION RANGE OF ELECTROOPTICAL SENSOR

COMPARISON OF POINT-SOURCE ALGORITHMS FOR OPTIMUM ACQUISITIO...

引用

conference on signal and data processing of small targets 1994

作者： JHA, US ROCKWELL INT CORP DIV AUTONET ELECTR SYSTANAHEIMCA 92803

ISBN: (纸本)0819415391

This paper examines a special class of signal processing technique called Minimum Variance Deconvolution (MVD) method and compares it with the commonly used Matched filtering and Wiener filtering based deconvolution processing in point source acquisition signal processing applications for Electro-Optical sensors. A step by step development of the batch and recursive MVD algorithm including comparison with the competing methods are presented in this paper.

关键词： Filtering (signal processing) Electronic filtering signal to noise ratio signal processing Deconvolution Digital filtering Electro optical sensors Algorithm development Electro optical modeling Error analysis

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Fast mutual exclusion

Fast mutual exclusion

引用

16th conference on signal and data processing of small targets

作者： Maskell, S Briers, M Wright, R QinetiQ Ltd Malvern Technol Ctr Malvern Worcs England

ISBN: (纸本)081945351X

A method is presented that circumvents the combinatorial explosion often assumed to exist when summing probabilities of joint association events in a multiple target tracking context. The approach involves no approximations in the summation and while the number of joint events grows exponentially with the number of targets, the computational complexity of the approach is substantially less than exponential. Multiple target tracking algorithms that use this summation include mutual exclusion(11,21) in a particle filtering context and the Joint Probabilistic data Association Filter,(7) a Kalman Filter based algorithm. The perceived computational expense associated with this combinatorial explosion has meant that such algorithms have been restricted to applications involving only a handful of targets. The approach presented here makes it possible to use such algorithms with a large number of targets.

关键词： Detection and tracking algorithms Filtering (signal processing) Electronic filtering Particle filters Particles

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Two-dimensional assignment with merged measurements using Lagrangian relaxation

Two-dimensional assignment with merged measurements using La...

引用

conference on signal and data processing of small targets

作者： Briers, M Maskell, S Philpott, M QinetiQ Ltd Malvern Technol Ctr Malvern Worcs England

ISBN: (纸本)0819450774

Closely spaced targets can result in merged measurements, which complicate data association. Such merged measurements violate any assumption that each measurement relates to a single target. As a result, it is not possible to use the auction algorithm in its simplest form (or other two-dimensional assignment algorithms) to solve the two-dimensional target-to-measurement assignment problem. We propose an approach that uses the auction algorithm together with Lagrangian relaxation to incorporate the additional constraints resulting-from the presence of merged measurements. We conclude with some simulated results displaying the concepts introduced, and discuss the application of this research within a particle filter context.

关键词： signal processing

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DIM POINT TARGET DETECTING FROM IMAGE SEQUENCES

DIM POINT TARGET DETECTING FROM IMAGE SEQUENCES

引用

conference on signal and data processing of small targets 1994

作者： LI, ZY SHEN, ZK NATL UNIV DEF TECHNOL DEPT EECHANGSHAPEOPLES R CHINA

ISBN: (纸本)0819415391

The technique of detecting and tracking of a moving point target is space-based background with low SNR is analyzed in this paper. An efficient method for detecting low speed targets is presented. The method simply uses multi-frame accumulating as the main operation in improving the output SNR. And it introduces candidate target records for target matching and recognition. The method is easy for hardware implementation that meets the demands of real time processing and low power consumption.

关键词： Target detection Target recognition signal to noise ratio Image processing Image storage Sensors Binary data Dysprosium Image sensors Computer programming

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Track testing for single targets in clutter

Track testing for single targets in clutter

引用

conference on signal and data processing of small targets 2000

作者： Willett, P Bar-Shalom, Y Univ Connecticut Storrs CT 06269 USA

ISBN: (纸本)0819436747

This paper concerns itself with the target-fi ee behavior of data association in clutter. There are a pair of main results. In the first, a new technique is developed for the detection of track loss. The basis is Page's (cusum) test, but a modification is given for the situation that the track-absent parameter (e.g. of mean of squared innovations) is not known. The result is a Page-style test with variable bias and threshold. The second matter of interest is the target-free distribution of the maximum-likelihood probabilistic data association (MLPDA) statistic. It is confirmed via importance sampling that a Gaussian distribution is not inappropriate;but the mean and variance of this distribution are different from those of the un-maximized log-likelihood surface. Guidance is given on the calculation of these.

关键词： Monte Carlo methods Palladium Detector development Filtering (signal processing) signal to noise ratio Computer simulations Convolution Motion measurement Sensors Target detection

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A small target tracking technique with data fusion of distributed sensor net

A small target tracking technique with data fusion of distri...

引用

conference on signal and data processing of small targets 1997

作者： Cheng, HW Sun, ZK Liu, Q Chen, YG Institute of Electronic Engineering National Univ. of Defense Technology Changsha Hunan 410073 China

ISBN: (纸本)0819425850

small targets defined in the paper are low-RCS targets or weak infrared emitting targets which are very difficult to track by a single sensor (a radar or an IRST) because the measurements gained by the sensor are usually unsuccessive. Although a single sensor can only observe the target in unsuccessive way, the sensor mt may sometimes track the target continuously by data fusion of the fractional trajectories or hits of the target from all sensors of the netted system. Typically, data fusion method of a distributed sensor net is track-to-track fusion that requires continuous track-level data(space vector estimates and their covariance matrices) from sensors in the net. For the case of small targets this condition can not be satisfied. In the paper, we derive a method to fuse the data of the small target from the system. The method includes data association and tracking. Special attention is pay to track initiation with Hough Transform for the association algorithm. Test and results are also given in the paper.

关键词： small target tracking data fusion distributed sensor net

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