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检索条件"任意字段=Conference on Signal and Data Processing of Small Targets 2010"

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signal processing Techniques for Maritime Surveillance with Skywave Radar

Signal Processing Techniques for Maritime Surveillance with ...

引用

International conference on Radar

作者： Turley, Mike D. E. Def Sci & Technol Org Edinburgh SA Australia

ISBN: (纸本)9781424423217

Detection and tracking of maritime targets using skywave radar is influenced by the propagation medium, interference environment and target scenario. Acquired data display distortion, fading, non-stationarity, and heterogeneity. Brief examples of data are given, then signal processing techniques are developed to provide robust adaptive Doppler processing, rejection of impulsive noise, improved CFAR using the Weibull distribution with robust two-parameter estimation, and a simple track-before-detect scheme for enhancing small SNR target detection performance.

关键词： Impulse noise

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Concurrent MAP data association and absolute bias estimation with an arbitrary number of sensors

Concurrent MAP data association and absolute bias estimation...

引用

20th conference on signal and data processing of small targets

作者： Kragel, Bret D. Danford, Scott Poore, Aubrey B. Numerica Corp Loveland CO USA

ISBN: (纸本)9780819471604

Bias estimation using objects with unknown data association requires concurrent estimation of both biases and optimal data association. This report derives maximum a posteriori (MAP) data association likelihood ratios for concurrent bias estimation and data association based on sensor-level track state estimates and their joint error covariance. Our approach is unique for two reasons. First, we include a bias prior that allows estimation of absolute sensor biases, rather than just relative biases. Second, we allow concurrent bias estimation and association for an arbitrary number of sensors. The two-sensor likelihood ratio is derived as a special case of the general M-sensor result.

关键词： multiple target tracking MAP bias estimation data association assignment problems track-to-track association

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Assurance regions in tracking

Assurance regions in tracking

引用

20th conference on signal and data processing of small targets

作者： Sworder, David D. Boyd, John E. Hutchins, R. G. Univ Calif San Diego Dept Elect & Comp Engn La Jolla CA 92093 USA Cub Def Applicat San Diego CA 92186 USA Naval Postgrad Sch Dept EECE Monterey CA 93943 USA

ISBN: (纸本)9780819471604

An assurance region at level p, A(P=p), is an area in motion space that contains the target with assigned probability p. It is on the basis of A(P=p) that an action is taken or a decision made. Common model-based trackers generate a synthetic distribution function for the kinematic state of the target. Unfortunately, this distribution is very coarse, and the resulting A(P=p) lack credibility. It is shown that a, map-enhanced, multiple model algorithm reduces the tracking, error and leads to a compact assurance region.

关键词： nonlinear filters target tracking data fusion

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Robust method for detecting an infrared small moving target based on the facet-based model

Robust method for detecting an infrared small moving target ...

引用

20th conference on signal and data processing of small targets

作者： Lee, Hwal-Suk Kim, Seokkwon Park, Dong-Jo Kim, Jieun Park, Changhan Korea Adv Inst Sci & Technol Sch EECS 373-1 Guseong Dong Taejon 305701 South Korea Agcy Def Dev Taejon South Korea SAMSUNG THALES Co Ltd Adv Technol R&D Ctr Yongin 446712 Gyeonggi South Korea

ISBN: (纸本)9780819471604

In this paper, a new condition for the target is proposed to increase the robustness of the facet-based detection method for zero-mean Gaussian noise. In the proposed algorithm, the pixels detected from the maximum extremum condition are checked further to discern if they are false maximum points in the proposed scheme. The experimental results show that the proposed algorithm is much more robust for zero-mean Gaussian noise than the conventional detection method.

关键词： infrared image small target detection cubic facet model Gaussian noise

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The probability of misassociation between neighboring targets

The probability of misassociation between neighboring target...

引用

20th conference on signal and data processing of small targets

作者： Areta, Javier A. Bar-Shalom, Yaakov Rothrock, Ronald Univ Connecticut Storrs CT 06269 USA Sparta Syst Inc Arlington VA 22209 USA

ISBN: (纸本)9780819471604

This paper presents procedures to calculate the probability that the measurement originating from an extraneous target will be (mis)associated with a target of interest for the cases of Nearest Neighbor and Global association. It is shown that these misassociation probabilities depend., under certain assumptions, on a particular - covariance weighted - norm of the difference between the targets' predicted measurements. For the Nearest Neighbor association, the exact solution, obtained for the case of equal innovation covariances, is based on a noncentral chi-square distribution. An approximate solution is also presented for the case of unequal innovation covariances. For the Global case an approximation is presented for the case of "similar" innovation covariances. In the general case of unequal innovation covariances where this approximation fails, an exact method based on the inversion of the characteristic function is presented. The theoretical results, confirmed by Monte Carlo simulations, quantify the benefit of Global vs. Nearest Neighbor association. These results are applied to problems of single sensor as well as centralized fusion architecture multiple sensor tracking.

关键词： Monte Carlo methods Sensors Matrices Target detection Detection and tracking algorithms Radar signal to noise ratio Algorithm development Distance measurement Sensor fusion

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Efficiency and sensitivity of methods for assessing ambiguity in data association decisions

Efficiency and sensitivity of methods for assessing ambiguit...

引用

20th conference on signal and data processing of small targets

作者： Kragel, Bret D. Herman, Shawn M. Roseveare, Nick J. Numerica Corp Loveland CO USA

ISBN: (纸本)9780819471604

The central problem in multitarget, multisensor surveillance is that of determining which reports from separate sensors arise from common objects. Due to stochastic errors in the source reports, there may be multiple data association hypotheses with similar likelihoods. Moreover, established methods for performing data association make fundamental modeling assumptions that hold only approximately in practice. For these reasons, it is beneficial to include some measure of uncertainty, or ambiguity, when reporting association decisions. In this paper, we perform an analysis of the benefits versus runtime performance of three methods of producing ambiguity estimates for data association: enumeration of the k-best data association hypotheses, importance sampling, and Markov Chain Monte Carlo estimation. In addition, we briefly examine the sensitivity of ambiguity estimates to violations of the stochastic model used in the data association procedure.

关键词： multitarget tracking data association importance sampling Markov Chain Monte Carlo murty's method k-best enumeration

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Track fusion with feedback for local trackers using MHT

Track fusion with feedback for local trackers using MHT

引用

20th conference on signal and data processing of small targets

作者： Danu, Daniel Lang, Tom Kirubarajan, T. McMaster Univ Dept Elect & Comp Engn Hamilton ON Canada Gen Dynam Canada Ottawa ON Canada

ISBN: (纸本)9780819471604

With current processing power, Multiple Hypothesis Tracking (MHT) becomes a feasible and powerful solution;however a good hypothesis pruning method is mandatory for efficient implementation. The availability of a continuously increasing number of tracking systems raises interest in combining information from these systems. The purpose of this paper is to propose a method of information fusion for such trackers that use MHT locally with local information sent in the form of sensor global hypotheses and the fusion center combining them into fused global hypotheses. The information extracted from the best fused global hypotheses, in the form of ranking of received sensor global hypotheses, is sent back to local trackers, for optimized pruning. Details of the method, in terms of sensor global hypotheses generation, evaluation, pruning at local sensors, association and fusion of sensor global hypotheses at fusion center, and usage of the information received as feedback from the fusion center are presented.

关键词： target tracking Multiple Hypothesis Tracking data fusion

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Hazardous material localization and person tracking

Hazardous material localization and person tracking

引用

20th conference on signal and data processing of small targets

作者： Wieneke, Monika Safenreiter, Konstantin Koch, Wolfgang FGAN FKIE D-53343 Wachtberg Germany

ISBN: (纸本)9780819471604

Timely recognition of threats can be significantly supported by security assistance systems that work continuously in time and call the attention of the security personnel in case of anomalies. We describe the concept and the realization of an indoor security assistance system for real-time decision support. data for the classification of persons are provided by chemical sensors detecting hazardous materials. Due to their limited spatio-temporal resolution, a single chemical sensor cannot localize this material and associate it with a person. We compensate this deficiency by fusing the output of multiple, distributed chemical sensors with kinematical data from laser-range-scanners. Both, tracking and fusion of tracks with chemical attributes can be processed within one single framework called Probabilistic Multiple Hypothesis Tracking (PMHT). An extension of PMHT for dealing with classification measurements (PMHT-c) already exists. We show how PMHT-c can be applied to associate chemical attributes to person tracks. This affords the localization of threads and a timely notification of the security personnel.

关键词： person tracking Probabilistic Multi-Hypothesis Tracking (PMHT) classification attributes data fusion security assistance systems

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An algorithm benchmark data suite for chemical and biological (chem/bio) defense applications

An algorithm benchmark data suite for chemical and biologica...

引用

20th conference on signal and data processing of small targets

作者： Slamani, Mohamed-Adel Fisk, Brian Chyba, Thomas Emge, Darren Waugh, Steve ITT Corp Adv Engn & Sci Div 2560 Huntington Ave Alexandria VA 22303 USA Edgewood Chem Biolog Ctr Aberdeen Proving Ground MD 21010 USA Def Threat Reduct Agcy Ft Belvoir VA 22060 USA

ISBN: (纸本)9780819471604

A Chem/Bio Defense Algorithm Benchmark is proposed as a way to leverage algorithm expertise and apply it to high fidelity Chem/Bio challenge problems in a high fidelity simulation environment. Initially intended to provide risk mitigation to the DTRA-sponsored US Army CUGR ACTD, its intent is to enable the assessment and transition of algorithms to support P3I of future spiral updates. The key chemical sensor in the CUGR ACTD is the Joint Contaminated Surface Detector (JCSD), a short-range stand-off Raman spectroscopy sensor for tactical in-the-field applications. The significant challenges in discriminating chemical signatures in such a system include, but are not limited to, complex background clutter and low signal to noise ratios (SNR). This paper will present an overview of the Chem-Bio Defense Algorithm Benchmark, and the JCSD Challenge Problem specifically.

关键词： signal to noise ratio

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Multitarget-multisensor tracking in an urban environment: A closed-loop approach

Multitarget-multisensor tracking in an urban environment: A ...

引用

20th conference on signal and data processing of small targets

作者： Barbosa, Patricia R. Chong, Edwin K. P. Suvorova, Sofia Moran, Bill Colorado State Univ 1373 Campus Delivery Ft Collins CO 80523 USA Intermap Technol Inc Englewood CO 80112 USA Univ Melbourne Parkville Vic 3010 Australia

ISBN: (纸本)9780819471604

When compared to tracking airborne targets, tracking ground targets on urban terrains brings a new set of challenges. Target mobility is constrained by road networks, and the quality of measurements is affected by dense clutter, multipath, and limited line-of-sight. We investigate the integration of detection, signal processing, tracking, and scheduling by exploiting distinct levels of diversity: (1) spatial diversity through the use of coordinated multistatic radars;(2) waveform diversity by adaptively scheduling the transmitted radar waveform according to the scene conditions;and (3) motion model diversity by using a bank of parallel filters, each one matched to a different maneuvering model. Specifically, at each scan, the waveform that yields the minimum one-step-ahead error covariance matrix determinant is transmitted;the received signal is then matched-filtered, and quadratic curve fitting is applied to extract range and azimuth measurements that are input to the LMIPDA-VSIMM algorithm for data association and filtering. Monte Carlo simulations are used to demonstrate the effectiveness of the proposed system on a realistic urban scenario. A more traditional open-loop system, in which waveforms are scheduled on a round-robin fashion and with no other modes of diversity available, is used as a baseline for comparison. Simulation results show that our closed-loop system significantly outperforms the baseline system, presenting both a reduction on the number of lost tracks, and a reduction on the volume of the estimation uncertainty ellipse. The interdisciplinary nature of this work highlights the challenges involved in designing a closed-loop active sensing platform for next-generation urban tracking systems.

关键词： target tracking detection filtering data association waveform scheduling

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