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检索条件"任意字段=16th Conference on Signal and Data Processing of Small Targets"

共 487 条记录，以下是141-150 订阅

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On expectation maximization applied to GMTI convoy tracking

On expectation maximization applied to GMTI convoy tracking

引用

14th conference on signal and data processing of small targets

作者： Koch, W FGAN FKIE D 53343 Wachtberg Neuenahrer Strasse 20 Germany

ISBN: (纸本)0819444782

Collectively moving ground targets are typical of a military ground situation and have to be treated as separate aggregated entities. For a long-range ground surveillance application with airborne GMTI radar we in particular address the task of track maintenance for ground moving convoys consisting of a small number of individual vehicles. In the proposed approach the identity of the individual vehicles within the convoy is no longer stressed. their kinematical state vectors are rather treated as internal degrees of freedom characterizing the convoy. which is considered as a collective unit. In this context, the Expectation Maximization technique (EM), originally developed for incomplete data problems in statistical inference and first applied to tracking applications by STREIT et al. [1, 2], seems to be a promising approach. We suggest to embed the EM algorithm into a more traditional Bayesian tracking framework for dealing with false or unwanted sensor returns. the proposed distinction between 'external' and 'internal' data association conflicts (i.e. those among the convoy vehicles) should also enable the application of sequential track extraction techniques introduced by VAN KEUK [3] for aircraft formations, providing estimates of the number of the individual convoy vehicles involved. Even with sophisticated signal processing methods (STAP: Space-Time Adaptive processing). ground moving vehicles can well be masked by the sensor specific clutter notch (Doppler blinding). this physical phenomenon results in interfering fading effects, which can well last over a longer series of sensor updates and therefore will seriously affect the track quality unless properly handled. Moreover, for ground moving convoys the phenomenon of Doppler blindness often superposes the effects induced by the finite resolution capability of the sensor. In many practical cases a separate modeling of resolution phenomena for convoy targets can therefore be omitted, provided the GMTI detectio

关键词： Ground Moving targets (GMT) Expectation Maximization (EM) Bayesian/Probabilistic Multiple Hypothesis Tracking (PMHT, MHT, PDA) Minimum Detectable Velocity (MDV) Doppler blinding sensor resolution phenomena

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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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UWB Microwave Monopulse Radar System for Breast Cancer Detection

UWB Microwave Monopulse Radar System for Breast Cancer Detec...

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4th International conference on signal processing and Communication Systems (ICSPCS)/12th International Symposium on DSP and Communication Systems (DSPCS)/9th Workshop on the Internet, Telecommunications and signal processing (WTSP)

作者： Bialkowski, Marek E. Wang, Yifan Abbosh, Amin Univ Queensland Sch Informat Technol & Elect Engn St Lucia Qld 4072 Australia

ISBN: (纸本)9781424479078

the concept of an Ultra Wideband (UWB) Monopulse Microwave Radar System for detection and location of breast cancer is described. the system uses a two-element Tapered Slot Antenna (TSA) array accompanied by a UWB 180 degrees hybrid which scans the breast. When the breast tissue features symmetry with respect to the array axis and the hybrid enables the 180 degrees out phase feeding operation, the array automatically eliminates background while extracting information about an off axis target. the data obtained from the scan is post-processed using a novel imaging algorithm to locate the target. the design of the required 2-element UWB array antenna and the 180 degrees hybrid is presented. the validity of the proposed breast cancer detection method is demonstrated in an example of a simple breast phantom formed by a cylindrical plastic container filled with a vegetable oil and small cylindrical targets.

关键词： UWB microwave monopulse radar system biomedical imaging breast cancer detection breast cancer location breast tissue cancer imaging algorithm microwave antenna arrays microwave imaging radar imaging small cylindrical targets tapered slot antenna array ult

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the probability of misassociation between neighboring targets

The probability of misassociation between neighboring target...

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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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Radar measurement noise variance estimation with several targets of opportunity - art. no. 62360M

Radar measurement noise variance estimation with several tar...

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18th conference on signal and data processing of small targets

作者： Osborne, Richard W., III Bar-Shalom, Yaakov Univ Connecticut Storrs CT USA

ISBN: (纸本)0819462926

A number of methods exist to track a target's uncertain motion through space using inherently inaccurate sensor measurements. A powerful method of adaptive estimation is the interacting multiple model (IMM) estimator. In order to carry out state estimation from the noisy measurements of a sensor, however, the filter should have knowledge of the statistical characteristics of the noise associated with that sensor. the statistical characteristics (accuracies) of real sensors, however, are not always available, in particular for legacy sensors. this paper presents a method of determining the measurement noise variances of a sensor by using multiple IMM estimators while tracking targets whose motion is not known - targets of opportunity. Combining techniques outlined in [1] and [3], the likelihood functions are obtained for a number of IMM estimators, each with different assumptions on the measurement noise variances. then a search is carried out to bracket the variances of the sensor measurement noises. the end result consists of estimates of the measurement noise variances of the sensor in question.

关键词： tracking noise estimation

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Poisson models for extended target and group tracking

Poisson models for extended target and group tracking

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17th conference on signal and data processing of small targets

作者： Gilholm, K Godsill, S Maskell, S Salmond, D QinetiQ Farnborough GU1 0LX Hants England

ISBN: (纸本)0819459186

It is common practice to represent a target group (or an extended target) as set of point sources and attempt to formulate a tracking filter by constructing possible assignments between measurements and the sources. We suggest an alternative approach that produces a measurement model (likelihood) in terms of the spatial density of measurements over the sensor observation region. In particular, the measurements are modelled as a Poisson process with a spatially dependent rate parameter. this representation allows us to model extended targets as an intensity distribution rather than a set of points and, for a target formation, it gives the option of modelling part of the group as a spatial distribution of target density. Furthermore, as a direct consequence of the Poisson model, the measurement likelihood may be evaluated without constructing explicit association hypotheses. this considerably simplifies the filter and gives a substantial computational saving in a particle filter implementation. the Poisson target-measurement model will be described and its relationship to other filters will be discussed. Illustrative simulation examples will be presented.

关键词： target tracking extended targets Poisson models particle filters

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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...

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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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Analysis and optimization of a class of nonlinear detection filters

Analysis and optimization of a class of nonlinear detection ...

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13th conference on signal and data processing of small targets

作者： Singer, PF Raytheon Co El Segundo CA 90245 USA

ISBN: (纸本)0819441872

It is well known that the matched filter is the optimal linear detection filter but, this allows for the possible existence of a nonlinear detection filter with better performance. this paper considers the class of nonlinear detection filters that are composed of a linear filter followed by an arbitrary point process. the result is general enough to include detection paradigm in which the signal model is not additive. the ROC (receiver operating characteristic) curve of a general point process is analyzed. this analysis reveals that nonreversibility and not nonlinearity of the point process is responsible for the improvement of the ROC curve. that is, an reversible point process, either linear or nonlinear, leaves the ROC curve unchanged. However, a nonreversible point process will alter the ROC curve. this result is used to define a canonical ROC curve which is then utilized to derive the optimal point process, Several simple forms of the point process are considered first then the general optimal point process is derived. the technique is illustrated with several examples. Results for the special cases of unimodal signal densities receive particular attention.

关键词： detection filter nonlinear nonreversible receiver operating characteristic signal model

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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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A range rate based detection technique for tracking a maneuvering target

A range rate based detection technique for tracking a maneuv...

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17th conference on signal and data processing of small targets

作者： Ru, JF Chen, HM Li, XR Chen, GH Univ New Orleans Dept Elect Engn New Orleans LA 70148 USA

ISBN: (纸本)0819459186

In this paper a novel approach for detecting unknown target maneuver using range rate information is proposed based on the generalized Page's test with the estimated target acceleration magnitude. Due to the high nonlinearity between the range rate measurement and the target state, a measurement conversion technique is used to treat rancre rate as a linear measurement in Cartesian coordinates so that a standard Kalman filter can be applied. the detection performance of the proposed algorithm is compared with that of existing maneuver detectors over various target maneuver motions. In addition, a model switching tracker based on the proposed maneuver detector is compared with the state-of-the-art IMM estimator. the results indicate the effectiveness of the maneuver detection scheme which simplifies the tracker design. the tracking performance is also evaluated using a steady state analysis.

关键词： Target detection Motion models Sensors Error analysis Filtering (signal processing) Detection and tracking algorithms Switching Motion estimation Performance modeling Radar

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