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检索条件"任意字段=Signal and Data Processing of Small Targets 1995 Conference"

共 783 条记录，以下是91-100 订阅

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Monopulse tracking of two unresolved Rayleigh targets

Monopulse tracking of two unresolved Rayleigh targets

引用

conference on signal and data processing of small targets 1997

作者： Blair, WD Watson, GA BrandtPearce, M Naval Surface Warfare Ctr. (United States) Univ. of Virginia (United States)

ISBN: (纸本)0819425850

When two targets are closely-spaced with respect to the resolution of a radar, the measurements of the two targets will be merged when the target echoes are not resolved in angle, range, or radial velocity (i.e., Doppler processing). Monopulse processing is considered for Direction-Of-Arrival (DOA) estimation of two unresolved Rayleigh targets with known relative Radar Cross Section (RCS). The probability distribution of the complex monopulse ratio is developed for two unresolved Rayleigh targets. The Fisher information matrix and Cramer Rao bounds are developed for the DOA estimation of two unresolved Rayleigh targets using a standard monopulse radar. When the two Rayleigh targets are separated by more than one-half of the radar beamwidth, DOA estimation is accomplished for each target by treating the other target as interference. When the two targets are separated by less than one-half of a beamwidth, the antenna boresight is pointed between the two targets, and the mean of the in-phase (i.e.,the real part) monopulse ratio and the variance of the in-phase and quadrature monopulse ratios are utilized to estimate the DOAs of the two targets. Simulation results that illustrate performance of the DOA estimators are given along with a simple tracking example.

关键词： radar signal processing target tracking sensor resolution

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Tracking targets using matched field observations

Tracking targets using matched field observations

引用

conference on signal and data processing of small targets

作者： Willett, PK Bishop, J Giannopoulos, E Univ Connecticut ECE Dept U 1157 Storrs CT 06269 USA

ISBN: (纸本)0819450774

The target tracking literature has traditionally been most interested in the "hit" model for the observations process, and the community has developed many techniques for data association. On the other hand, matched field processing (MFP) research has focused on signal processing with the main emphasis on target detection and localization. Treatments of combined tracking/MFP systems are not common. but most concentrate on signal processing, with the idea that a "track" is really a sequence or track-segment of detections that make sense from dynamics considerations. Thus, here we explore the MFP tracking problem, with the key that we attempt to use traditional target-tracking algorithms. In particular. we use an IMMPDAF-AI (interacting multiple-model probabilistic data association filter with amplitude information). It is shown that the use of such an advanced tracking algorithm - plus a number of MFP-specific refinements - produces tracking performance that is far superior to that obtained for a more traditional tracking (a strongest-neighbor Kalman filter), with the added advantage of a significantly reduced numerical load as measured in terms of the number of MFP replicas to be computed.

关键词： Target tracking matched field processing passive sonar interacting multiple models probabilistic data association filter

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A performance model for unresolved target detection using multispectral infrared data

A performance model for unresolved target detection using mu...

引用

conference on signal and data processing of small targets

作者： Singer, PF Sasaki, DM Raytheon Syst Co EO E1 El Segundo CA 90245 USA

ISBN: (纸本)0819428221

The detection of dim targets in heavy clutter requires large gains in the SCR (signal-to-clutter ratio). Gains of the required magnitude have been obtained with space-temporal processing. However, in many cases these gains are either difficult or expensive to realize. If the range to the clutter is small relative to the clutter velocity, the temporal processing will need to include scene registration and optical flow correction. Scene registration is computationally expensive especially for large search volumes. The correction of optical flow is both expensive and typically less than satisfactory. The spectral dimension provides an alternative to the temporal dimension. Since the data in each of the spectral bands is collected simultaneously or nearly so, the problems of registration and optical flow are eliminated. This paper considers the performance of the multi-spectral infrared bands. Dual band performance results comparing space spectral processing with space temporal will be shown. An analytic model of the probability of false alarm as a function of the number of spectral bands is presented. A comparison of this model to experimental results using multi-spectral IRST data is given.

关键词： dualband multispectral space-spectral detection ROC

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Target selection using neural networks

Target selection using neural networks

引用

14th conference on signal and data processing of small targets

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

ISBN: (纸本)0819444782

Target selection is the task of assigning a value or priority to various targets in a scenario. This priority is usually determined by the threat the target poses on the defender in addition to its vulnerability to possible measures to be taken by the defender. In this study, we describe a target selection technique based on neural networks. The utility or value of each target is assumed to be an unknown function acting on certain features of the target such as size, intensity, speed and direction of movement. Neural networks used in the context of function estimation is a viable candidate for determining this unknown function for generating target priorities. Various. neural network configurations are examined and simulation results are presented.

关键词： Neural networks Target detection Neurons Ranging signal processing Image processing Infrared imaging Infrared radiation Sensors databases

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small curvature particle flow for nonlinear filters

Small curvature particle flow for nonlinear filters

引用

conference on signal and data processing of small targets

作者： Daum, Fred Huang, Jim Raytheon Co Woburn MA USA

ISBN: (纸本)9780819490711

We derive seven new particle flow algorithms for nonlinear filters based on the small curvature condition inspired by fluid dynamics. We find it extremely interesting that this physically motivated condition generalizes two of our previous exact flow algorithms, namely incompressible flow and Gaussian flow. We derive a new algorithm to compute the inverse of the sum of two linear differential operators using a second homotopy, similar to Feynman's perturbation theory for quantum electrodynamics as well as Gromov's h-principle.

关键词： particle filter nonlinear filter particle flow Kalman filter extended Kalman filter

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small extending target precision tracking with dual-infrared imaging sensors

Small extending target precision tracking with dual-infrared...

引用

conference on signal and data processing of small targets 1999

作者： Liang, HC Ni, GQ Zhu, ZF Xu, GX Pan, AJ Song, B Beijing Inst Technol Dept Optoelect Engn Beijing 100081 Peoples R China

ISBN: (纸本)0819432954

It is a challenging problem to track point source targets and small extending ones in clutter. Only using single-image sensor is usually not adequate to meet the requirement of a multi-target tracking (MTT) system. Carrying out the measurement through two infrared waveband image sensors, and fusing efficiently measurement data of both sensors, we can track small extending targets precisely and improve the performance of the MTT system. In this paper, the multi-target tracking method based on 3 similar to 5 mu m and 8 similar to 12 mu m infrared image sensors is introduced. The mission scenario is thought as tracking air target. The algorithm of the target image centroid estimator is discussed. In order to improve the precision of target tracking, the data fusion algorithm with Kalman filter is described for the target vector feature. The simulation results indicate that the target tracking precision can be improved by tracking small extending targets with dual-infrared image sensors.

关键词： data fusion target tracking Kalman filter small extending target infrared imaging

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OPTIMUM DETECTION IN DUAL-CHANNEL GAUSSIAN data WITH LOCALIZED INTERFERENCE

OPTIMUM DETECTION IN DUAL-CHANNEL GAUSSIAN DATA WITH LOCALIZ...

引用

conference on signal and data processing of small targets 1994

作者： WARREN, RE SRI INT MENLO PKCA 94025

ISBN: (纸本)0819415391

This paper derives a likelihood-ratio detector for bivariate time-series data having target- and correlated non-target-bearing components with randomly distributed, single-cell spike noise in one or both channels. After defining the detection problem explicitly, the detector is constructed as an analytic expression. A specific implementation of the approach is presented using a bivariate first-order autoregressive model for the correlation structure of the data. A computer model for the detector is constructed, and results using simulated data verify the usefulness of the approach in removing strong pike noise without damage to the target signal.

关键词： Sensors Target detection data modeling Autoregressive models Computer simulations Detector development Interference (communication) Matrices signal detection Picosecond phenomena

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Bayesian approach to avoiding track seduction

Bayesian approach to avoiding track seduction

引用

14th conference on signal and data processing of small targets

作者： Salmond, DJ Everett, NO QinetiQ Farnborough GU14 0LX Hants England

ISBN: (纸本)0819444782

The problem of maintaining track on a primary target in the presence spurious objects is addressed. Recursive and batch filtering approaches are developed. For the recursive approach, a Bayesian track splitting filter is derived which spawns candidate tracks if there is a possibility of measurement misassociation. The filter evaluates the probability of each candidate track being associated with the primary target. The batch filter is a Markov-chain Monte Carlo (MCMC) algorithm which fits the observed data sequence to models of target dynamics and measurement-track association. Simulation results are presented.

关键词： Bayesian methods target tracking multiple targets JPDAF MCMC

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Improved Multiframe Association for Tracking Maneuvering targets

Improved Multiframe Association for Tracking Maneuvering Tar...

引用

conference on signal and data processing of small targets

作者： Habtemariam, Biruk K. Tharmarasa, R. Nandakumaran, N. McDonald, M. Kirubarajan, T. McMaster Univ ECE Dept Hamilton ON Canada Curtin Univ Technol Perth WA Australia Def Res & Dev Canada Ottawa ON Canada

ISBN: (纸本)9780819487476

data association is the crucial part of any multitarget tracking algorithm in a scenario with multiple closely spaced targets, low probability of detection and high false alarm rate. Multiframe assignment, which solves the data association problem as a constrained optimization, is one of the widely accepted methods to handle the measurement origin uncertainty. If the targets do not maneuver, then multiframe assignment with one or two frames will be enough to find the correct data association. However, more frames must be considered in the data association for maneuvering targets. Also, a target maneuver might be hard to detect when maneuvering index, which is the function of sampling time, is small. In this paper, we propose an improved multiframe data association with better cost calculation using backward multiple model recursion, which increases the maneuvering index. The effectiveness of the proposed algorithm is demonstrated with simulated data.

关键词： multiframe data association interacting multiple model maneuvering targets smoothing out-of-sequence measurements

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NEW EXACT NONLINEAR FILTERS - THEORY AND APPLICATIONS

NEW EXACT NONLINEAR FILTERS - THEORY AND APPLICATIONS

引用

conference on signal and data processing of small targets 1994

作者： DAUM, FE RAYTHEON CO DIV EQUIPMENTWAYLANDMA 01778

ISBN: (纸本)0819415391

A new exact recursive filter is derived for nonlinear estimation problems. The new nonlinear theory includes the Kalman filter as a special case. This filter is practical to implement in real- time applications, and it has a computational complexity that is comparable to the Kalman filter. The measurements are made in discrete time, but the random process to be estimated evolves in continuous time.

关键词： Nonlinear filtering Filtering (signal processing) Time metrology Digital filtering Radar Electronic filtering Error analysis Differential equations Palladium Process modeling

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