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共 168 条记录，以下是71-80 订阅

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An improved clustering approach for multiplatform data fusion

An improved clustering approach for multiplatform data fusio...

引用

13th conference on signal and data processing of small targets

作者： de Waard, HW Elgersma, V Thales Naval Nederland BV NL-7550 GD Hengelo Netherlands

ISBN: (纸本)0819441872

In the first part of the paper a new solution is proposed for distributed multiplatform data fusion, in which the different platforms exchange only compressed, track-related information. An improved clustering concept is introduced based on the premise that a cluster call contain a number of independent components, and based oil the definition of a marginal bearing density function for the measurements produced by a certain track. Based oil the found independent components new clusters can be formed. In the second part of the paper experimental evidence for the existence of independent components is presented. Furthermore, for the simulated multiplatform system experimental results concerning platform tracking and the reduction in the use of computer computation time, based oil implemented measures from,(1) are presented.

关键词： Distributed multiplatform data fusion multiple target tracking data-association M(ultiple) H(ypothesis) T(racking) independent component standard building block

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Mysterious computational complexity of particle filters

Mysterious computational complexity of particle filters

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14th conference on signal and data processing of small targets

作者： Daum, F Huang, J Raytheon Elect Syst Sudbury MA 01776 USA

ISBN: (纸本)0819444782

Particle filtering (PF) is a relatively new method to solve the nonlinear filtering problem, which is very general and easy to code. the main issue with PF is the large computational complexity. In particular, for typical low dimensional tracking problems, the PF requires 2 to 4 orders of magnitude more computer throughput than the EKF, to achieve the same accuracy. It has been asserted that the PF avoids the curse of dimensionality, but there is no formula or theorem that bounds or approximates the computational complexity of the PF as a function of dimension (d). In this paper, we will derive a simple back-of-the-envelope formula that explains why a carefully designed PF should mitigate the curse of dimensionality for typical tracking problems, but that it does not avoid the curse of dimensionality in general. this new theory is related to the fact that the volume of the d dimensional unit sphere is an amazingly small fraction of the d dimensional unit cube, for large d.

关键词： Error analysis Monte Carlo methods Nonlinear filtering Particles Particle filters Filtering (signal processing) Optical spheres Electronic filtering Probability theory Statistical analysis

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Discriminating small extended targets at sea from clutter and other classes of boats in infrared and visual light imagery

Discriminating small extended targets at sea from clutter an...

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20th conference on signal and data processing of small targets

作者： van den Broek, Sebastiaan P. Bouma, Henri Degache, Marianne A. C. TNO Def Secur & Safety NL-2509 JG The Hague Netherlands

ISBN: (纸本)9780819471604

Operating in a coastal environment, with a multitude of boats of different sizes, detection of small extended targets is only one problem. A further difficulty is in discriminating detections of possible threats from alarms due to sea and coastal clutter, and from boats that are neutral for a specific operational task. Adding target features to detections allows filtering out clutter before tracking. Features can also be used to add labels resulting from a classification step. Both will help tracking by facilitating association. Labeling and information from features can be an aid to an operator, or can reduce the number of false alarms for more automatic systems. In this paper we present work on clutter reduction and classification of small extended targets from infrared and visual light imagery. Several methods for discriminating between classes of objects were examined, with an emphasis on less complex techniques, such as rules and decision trees. Similar techniques can be used to discriminate between targets and clutter, and between different classes of boats. Different features are examined that possibly allow discrimination between several classes. data recordings are used, in infrared and visual light, with a range of targets including rhibs, cabin boats and jet-skis.

关键词： classification clutter reduction target recognition small targets boats jet-ski

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Maximum likelihood angle extractor in the presence of sea-surface multipath

Maximum likelihood angle extractor in the presence of sea-su...

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14th conference on signal and data processing of small targets

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

ISBN: (纸本)0819444782

In the presence of sea-surface multipath monopulse radar signals from a low elevation target have three alternative paths in addition to the direct (radar-to-target) path due to reflections from the sea surface. the specular reflection causes significant signal fading. the diffuse reflection causes an approximately constant bias to the in-phase component of the monopulse ratio, which is the standard extractor of the direction of arrival (DOA) in the monopulse processing. the diffuse reflection also causes higher standard deviation to the in-phase component of the monopulse ratio. In this paper we propose a maximum likelihood (ML) angle extraction technique for low elevation targets of known average signal strength having a Rayleigh fluctuation. the results show that this method reduces the error of the estimated angle compared to the conventional monopulse ratio estimator. Subsequently, the ML angle extractor is modified for the unknown average signal strength case. this modified angle extractor has only a small performance degradation compared with the known average signal strength case, but it performs much better than the monopulse ratio based estimator. this angle extractor reduces the root mean square error (RMSE) by more than 50% in the signal processing stage when used in a low flying target (sea skimmer) tracking scenario.

关键词： Radar Reflection signal to noise ratio Specular reflections Error analysis signal processing Detection and tracking algorithms Silicon Analytical research Computer engineering

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Expected likelihood for tracking in clutter with particle filters

Expected likelihood for tracking in clutter with particle fi...

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14th conference on signal and data processing of small targets

作者： Marrs, A Maskell, S Bar-Shalom, Y QinetiQ Ltd Malvern Technol Ctr Malvern Worcs England

ISBN: (纸本)0819444782

the standard approach to tracking a single target in clutter, using the Kalman filter or extended Kalman filter, is to gate the measurements using the predicted measurement covariance and then to update the predicted state using probabilistic data association. When tracking with a particle filter, an analog to the predicted measurement covariance is not directly available and could only be constructed as an approximation to the current particle cloud. A common alternative is to use a form of soft gating, based upon a Student's-t likelihood, that is motivated by the concept of score functions in classical statistical hypothesis testing. In this paper, we combine the score function and probabilistic data association approaches to develop a new method for tracking in clutter using a particle filter. this is done by deriving an expected likelihood from known measurement and clutter statistics. the performance of this new approach is assessed on a series of bearings-only tracking scenarios with uncertain sensor location and non-Gaussian clutter.

关键词： tracking probabilistic data association particle filters

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A dynamic approach to efficiently clustering and predicting groups for moving targets

A dynamic approach to efficiently clustering and predicting ...

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16th conference on signal and data processing of small targets

作者： Ma, DY Zhang, AD SUNY Buffalo Dept Comp Sci & Engn Buffalo NY 14260 USA

ISBN: (纸本)081945351X

Effective and efficient approaches to monitor and manage maneuvering objects are of great importance in various applications, such as wide battlefields, traffics, and wireless communications. Modern airborne radar sensors can provide wide-area surveillance coverage of ground activities. the huge volume of radar data renders it impractical and inefficient to examine all the activities of individual moving object. Clustering moving objects and predicting motion tendencies of large groups are becoming a crucial issue for optimizing resource distribution and formulating sound decisions. However, most traditional clustering techniques are static-object-oriented and not effective at clustering maneuvering objects. In addition, the radar data intermittence and noise data, which are caused by extraneous objects and stationary clutter background, are major difficulties in clustering and predicting groups. In this paper, we present a dynamic-object-oriented clustering approach to detecting and predicting large group activities over time. We propose a "core member" concept to support dynamic-object-oriented clustering and to mitigate the effects of data intermittence and noise data. In general, some special targets always tend to remain in a constant group and stay near the center of that group. To a large extent, the movement of these targets represents the activity of the entire group. To exploit this characteristic, we consider these special targets to be core members of their own cluster. the movements of the core members can help us detect clusters and predict their future movements. the performance and results of the application of our approach to CASTFOREM data sets are also presented.

关键词： Radar Detection and tracking algorithms Filtering (signal processing) Target detection Electronic filtering Sensors data modeling Surveillance Wireless communications signal detection

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data association in target tracking using priority queues

Data association in target tracking using priority queues

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17th conference on signal and data processing of small targets

作者： Sinha, A Kirubarajan, T Farooq, M McMaster Univ Dept Elect & Comp Engn ETFLab Hamilton ON Canada

ISBN: (纸本)0819459186

data association is one of the main components of target tracking. While, in its simplest form, data association links a list of tracks to a list of measurements or links two lists of measurements (2-D association), the more complex problem involves assignment of multiple number of such lists (S-D association where S > 3). In target tracking, the presence of false detections (false alarms) and the absence of detections from some targets (missed detections) complicate the problem of data association further. In this work, we explore the possibility of applying track ordering in priority queues to solve the association problem more efficiently. the basic component of our algorithm is to form priority queues by permutations of the tracks. Each queue is served on a first-come-first-served basis, i.e., each track is assigned to the best measurement available based on its turn in the queue. It can be shown that the best solution to the 2-D problem can be obtained from one of these queues. However, the solution is computationally expensive even for a moderate number of targets. In this paper we show that due to redundancy only a small fraction of the total number of permutations is required to be evaluated to obtain the best solution.

关键词： Multisensor-multitarget tracking 2-D assignment algorithms priority queue m-best solutions

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Tracking of low-observable small targets against clutter

Tracking of low-observable small targets against clutter

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13th conference on signal and data processing of small targets

作者： Shue, L Venkateswarlu, R Lim, ET Nanyang Technol Univ Ctr Signal Proc Singapore 639798 Singapore

ISBN: (纸本)0819441872

Detection and tracking of low-observable moving targets against heavy clutter in a sequence of infrared images is an important research area. the focus of research in this area is to reliably pick up the most potential targets, track the targets with varying speed and direction, and at the same time reduce the false alarm rate to ala acceptable level. However, there is no single method that works equally well hi all situations. this paper presents an integrated algorithm based on area-correlation tracker (ACT) and Kalman filter for improving ACT performance for targets with varying speed and direction. Divergence and loss of target when the target is stationary are the two typical problems associated with ACT. In our algorithm, we propose to overcome these shortcomings by introducing an online procedure for updating (or not updating in the case of occlusions) the reference template, in conjunction with linear predictions by using a Kalman filter.

关键词： small target image registration area-correlation Kalman filter

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Bias estimation using targets of opportunity

Bias estimation using targets of opportunity

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19th conference on signal and data processing of small targets

作者： Kragel, Bret D. Danford, Scott Herman, Shawn M. Poore, Aubrey B. Numer Corp 4850 Hahns Peak Dr Loveland CO 80538 USA

ISBN: (纸本)9780819468475

Fusion of data from multiple sensors can be hindered by systematic errors known as biases. Specifically, the presence of biases can lead to data misassociation and redundant tracks. Fortunately, if an estimate of the unknown biases can be obtained, the measurements and transformations for each sensor can be debiased prior to fusion. In this paper, we present an algorithm that uses targets of opportunity in the sensor field-of-view for online estimation of time-variant biases. the algorithm uses the singular value decomposition (SVD) to automatically handle the issue of parameter observability during tracking, allowing for shorter estimation windows and more accurate bias estimation. Our approach extends the novel methods proposed in the companion paper(1) by Herman and Poore that used the SVD within a nonlinear least-squares estimator to handle the issue of parameter observability during offline estimation of time-invariant biases using truth data.

关键词： bias estimation sensor registration gridlock nonlinear least-squares singular value decomposition bias observability

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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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