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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331-340 订阅

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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...

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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

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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...

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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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Passive tracking with sensors of opportunity using passive coherent location - art. no. 69691F

Passive tracking with sensors of opportunity using passive c...

引用

20th conference on signal and data processing of small targets

作者： Subramaniam, Mahes Tharmarasa, R. McDonald, Mike Kirubarajan, T. McMaster Univ ECE Dept ETF Lab Hamilton ON Canada

ISBN: (纸本)9780819471604

Passive coherent location (PCL), which uses the commercial signals as illuminators of opportunity, is an emerging technology in air defense systems. The advantages of PCL are low cost, low vulnerability to electronic counter measures, early detection of stealthy targets and low-altitude detection. However, limitations of PCL include lack of control over illuminators, poor bearing accuracy, time-varying sensor parameters and limited observability. In this paper, multiple target tracking using PCL with high bearing error is considered. In this case, the challenge is to handle high nonlinearity due to high measurement error. In this paper, we implement the converted measurement Kalman filter, unscented Kalman filter and particle filter based PHD filter for PCL radar measurements and compare their performances.

关键词： passive radar system passive coherent location multitarget tracking data association covert tracking sensors of opportunity

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An advanced missile warning processing suite

An advanced missile warning processing suite

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20th conference on signal and data processing of small targets

作者： Montgomery, Joel B. Sanderson, Richard B. McCalmont, John F. Johnson, R. S. McDermott, D. J. Taylor, M. J. M&M Aviat 2302 Schnebly Rd Spring Valley OH 45370 USA Air Force Res Lab Wright Patterson AFB OH 45433 USA MacAulay Brown Dayton OH 45430 USA Gen Dynam Corp Dayton OH 45430 USA

ISBN: (纸本)9780819471604

Effective missile warning and countermeasures remain an unfulfilled goal for the Air Force and others in the DOD community. To make the expectations a reality, newer sensors exhibiting the required sensitivity, field of regard, and spatial resolution are being developed and transitioned. The largest concern is in the first stage of a missile warning system: detection, in which all targets need to be detected with a high confidence and with very few false alarms. Typical fielded sensors are limited in their detection capability by either lack of sensitivity or by the presence of heavy background clutter, sun glints, and inherent sensor noise. Many threat environments include false alarm sources like burning fuels, flares, exploding ordinance, arc welders, and industrial emitters. Multicolor discrimination has been shown as one of the effective ways to improve the performance of missile warning sensors, particularly for heavy clutter situations. Its utility has been demonstrated in multiple demonstration and fielded systems. New exploitations of background and clutter spectral contents, coupled with advanced spatial and temporal filtering techniques, have resulted in a need to have a new baseline algorithm on which future processing advances may be judged against. This paper describes the AFRL Suite IIIc algorithm chain and its performance against long-range dim targets in clutter.

关键词： infrared background suppression multicolor missile warning point targets discrimination algorithm clutter rejection backgrounds real-time processing parallel processing

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Determining the optimal time frame for multisensor track correlation

Determining the optimal time frame for multisensor track cor...

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20th conference on signal and data processing of small targets

作者： Ehrman, Lisa M. Burns, Paul D. Blair, W. Dale Georgia Inst Technol Sensors & Electromagnet Applicat Lab Atlanta GA 30332 USA

ISBN: (纸本)9780819471604

Conventional algorithms for track association (termed "correlation" by convention) employ algorithms which are applied to all sensor tracks at a specific time. The overall value of sensor networks for data fusion is closely tied to the reliability of correct association of common objects tracked by the sensors. Multisensor architectures consisting of gaps in target coverage requires that tracks must be propagated substantially forward or backward to a common time for correlation. This naturally gives rise to the question: at which time should track correlation be performed? In the conventional approach, a two-sensor correlation problem would be solved by propagating the first sensor's tracks forward to the update time (current time) of the tracks from the second sensor. We question this approach by showing simulation results that indicate that the current time can be the worst time to correlate. In addition, a methodology for calculating the approximate optimal correlation time for linear-Gaussian tracking problems is provided.

关键词： Sensors Mahalanobis distance 3D acquisition Detection and tracking algorithms Missiles Sensor networks data fusion Defense and security Radio propagation Reliability

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