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16th conference on signal and data processing of small targets

作者： Willett, P Blair, WD Ogle, T Univ Connecticut Storrs CT USA

ISBN: (纸本)081945351X

A monopulse radar is able to derive accurate angular measurements via intelligent processing of its sum and difference channel returns. Recently there have emerged techniques for angular estimation of several unresolved targets. meaning targets that are. in principle, merged within the same radar beam, can be extracted separately. The key is the joint exploitation of information in several range bins. Here we show the performance of this approach in a high-fidelity simulation: we observe considerable improvement in track RMSE, but little corresponding, gain in track completeness. Coupled with a hidden Markov model on target number, however, the performance is impressive.

关键词： radar target tracking radar signal processing resolution

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The JPDAF in Practical Systems: Approximations

The JPDAF in Practical Systems: Approximations

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conference on signal and data processing of small targets 2010

作者： Romeo, Kevin Crouse, David F. Bar-Shalom, Yaakov Willett, Peter Univ Connecticut Dept Elect & Comp Engn Storrs CT 06269 USA

ISBN: (纸本)9780819481627

In this paper we look at various algorithms for approximating the target-measurement association probabilities of the Joint Probabilistic data Association Filter (JPDAF). We consider their computational complexity and compare their performance with respect to the Mean Optimal Subpattern Assignment (MOSPA) statistic in a scenario involving closely-spaced targets.

关键词： Detection and tracking algorithms Target detection Monte Carlo methods Computer simulations Error analysis Time metrology Algorithm development Computing systems data processing signal processing

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Detection of small targets and their Characterization Based on their Formation using an Image Feature Network-Based Object Recognition Algorithm

Detection of Small Targets and their Characterization Based ...

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conference on signal and data processing of small targets

作者： Straub, Jeremy Univ N Dakota Dept Comp Sci Grand Forks ND 58202 USA

ISBN: (纸本)9781628410297

small target detection and classification is problematic. For targets that operate as part of a cluster, classification can be performed based on the characteristics of the cluster's operations, instead of trying to identify an individual cluster-member directly. This paper presents an algorithm for object identification based on comparing networks of point-to-point distances between features identified by an image feature detection algorithm. It discusses the alterations required to make the algorithm suitable for performing cluster-formation based characterization of small targets from point or near-point source data. An analysis of the algorithm's performance is presented and it efficacy for this application assessed.

关键词： small target detection and classification point targets classification decision cluster object identification cluster-formation based characterization of small targets

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IMMPDAF solution for the tracking and radar management benchmark with merged measurements and multipath

IMMPDAF solution for the tracking and radar management bench...

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conference on signal and data processing of small targets

作者： Sinha, A Kirubarajan, T Bar-Shalom, Y Univ Connecticut Dept Elect & Comp Engn Storrs CT 06268 USA

ISBN: (纸本)0819450774

Radar signal processing is a key part in tracking closely spaced targets and targets in the presence of sea-surface-induced multipath. These issues are the salient features of the benchmark problem for tracking unresolved targets combined with radar management, for which this paper presents the only complete solution to date. In this paper a modified version of a recently developed "superresolution" maximum likelihood (ML) angle estimator for closely spaced targets as well as targets in the presence of multipath are presented. Efficient radar resource allocation algorithms for two closely spaced targets and targets flying close to the sea surface are also presented. Finally, the IMMPDAF (interacting multiple model estimator with probabilistic data association filter modules) is used to track these targets. It is found that a two-model IMMPDAF performs better than the three model version used in the previous benchmark. Also, the IMMPDAF with a coordinated turn model works better than the one using a Wiener process acceleration model. The signal processing and tracking algorithms presented here, operating in a feedback manner, form a comprehensive solution to the most realistic tracking and radar management problem to date.

关键词： Radar signal processing Performance modeling Detection and tracking algorithms Target detection signal to noise ratio Super resolution Sensors data modeling Radar signal processing

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Detection of small IR objects using wavelets, matched subspace detectors, and registration

Detection of small IR objects using wavelets, matched subspa...

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14th conference on signal and data processing of small targets

作者： Hewer, G Kuo, W Kenney, C Hanson, G Bobinchak, J USN Air Warfare Ctr China Lake CA 93555 USA

ISBN: (纸本)0819444782

Infrared sensors and advanced signal processing are used to detect small (or "point") targets in highly cluttered and noisy environments. In this paper, a wavelet detection algorithm and tracking of small targets in clutter will be discussed. A new registration algorithm based on optical flow estimates with matched subspace detectors against small maneuverable targets is also discussed. Both detectors incorporate adaptive constant false alarm rate (CFAR) detection statistics. Simulation of the detection and tracking algorithms using an unclassified database with a helicopter target and platform for the video cameras is summarized.

关键词： wavelets matched subspace detector registration

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Unified sensor management in unknown, dynamic clutter

Unified sensor management in unknown, dynamic clutter

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conference on signal and data processing of small targets 2010

作者： Mahler, Ronald El-Fallah, Adel Lockheed Martin MS2 (United States) Scientific Systems Co. Inc. (United States)

ISBN: (纸本)9780819481627

In recent years the first author has developed a unified, computationally tractable approach to multisensor-multitarget sensor management. This approach consists of closed-loop recursion of a PHD or CPHD filter with maximization of a "natural" sensor management objective function called PENT (posterior expected number of targets). In this paper we extend this approach so that it can be used in unknown, dynamic clutter backgrounds.

关键词： Sensors Target detection Process modeling Space sensors Current controlled current source data processing Electronic filtering Probability theory signal detection signal processing

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ADAPTIVE ANTENNA SPACE-TIME processing TECHNIQUES TO SUPPRESS PLATFORM SCATTERED CLUTTER FOR AIRBORNE RADAR

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IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS 1995年第1期31卷 382-389页

作者： BARILE, EC GUELLA, TP LAMENSDORF, D MITRE CORP BEDFORDMA 01730

Advanced airborne radar may require adaptive space-time processing (STP) to detect small targets at long ranges. STP is a multidimensional adaptive filter that resolves received radar data into a spectrum of plane waves in angular and Doppler frequency coordinates. The platform of an airborne radar can scatter incident signals into the antenna, spreading the spectra of the clutter signals so that it overlaps the target signal and therefore increases the false alarm rate. To reduce the processing requirements of a full STP filter, a suboptimal architecture with fewer degrees of freedom is demonstrated and compared with the optimal architecture.

关键词： Doppler radar adaptive filters adaptive signal processing airborne radar interference suppression radar clutter Doppler frequency coordinates adaptive antenna space-time processing adaptive space-time processing clutter signals false alarm

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SUPER NONCOHERENT INTEGRATION - ANALYSIS OF PERFORMANCE

SUPER NONCOHERENT INTEGRATION - ANALYSIS OF PERFORMANCE

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conference on signal and data processing of small targets 1994

作者： DAUM, F RAYTHEON CO WAYLANDMA 01778

ISBN: (纸本)0819415391

This paper analyzes a new method to detect targets. The new method, called `super noncoherent integration' (SNCI), can improve overall detection performance by typically 5 dB to 10 dB relative to conventional noncoherent integration. A simple back-of-the-envelope formula is derived which quantifies the performance improvement of SNCI. Conventional noncoherent integration (CNCI) uses only amplitude measurements to distinguish targets from noise or clutter. In contrast, SNCI uses amplitude data in addition to: monopulse data, quadrature monopulse data, range and Doppler data over a sequence of N transmitted radar waveforms.

关键词： signal to noise ratio Doppler effect Radar Target detection Sensors Filtering (signal processing) Detection and tracking algorithms Error analysis Infrared sensors signal detection

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Sidelobe reduction for efficient detection of multiple radar targets

Sidelobe reduction for efficient detection of multiple radar...

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conference on signal and data processing of small targets

作者： Deng, H Univ New Orleans Dept Elect Engn New Orleans LA 70148 USA

ISBN: (纸本)0819450774

With multiple radar targets the sidelobe of matched filtering outputs from the stronger targets become the interferences for the detection of weaker targets. An effective approach based on traditional CLEAN algorithm is proposed for sidelobe reduction for the matched filtering output of binary coding radar signals. A novel multilevel sidelobe reduction method is also developed for closely located multiple targets of nearly equally strong scatterings. The effectiveness of the sidelobe reduction algorithms is demonstrated through the numerous processing results.

关键词： radar target detection pulse compression CLEAN algorithms interference reduction

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Identity Variance for Multi-Object Estimation

Identity Variance for Multi-Object Estimation

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conference on signal and data processing of small targets

作者： Crouse, David F. Willett, Peter Univ Connecticut Dept Elect & Comp Engn Storrs CT 06269 USA

ISBN: (纸本)9780819487476

We define the notion of an "identity variance" for expressing the level of uncertainty between target identities in a PDF representing the states of multiple targets. This, coupled with an OSPA covariance introduced in past work, can form a basis for evaluating both the accuracy of the state estimates as well as the confidence in the identities of the states. A potential application of the identity variance is as a criterion for choosing between waveforms optimized for producing accurate position estimates versus good classification information on a multifunction radar.

关键词： Error analysis Radar Matrices Particles Computer engineering Current controlled current source data analysis data processing Particle filters signal processing

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