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检索条件"任意字段=IET Seminar on Target Tracking and Data Fusion: Algorithms and Applications"

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Bearings-only TMA on manoeuvring target a Gaussian mixture approach

Bearings-only TMA on manoeuvring target a Gaussian mixture a...

引用

2008 iet seminar on target tracking and data fusion: algorithms and applications

作者： D. Laneuville SIS Division DCNS Toulon France

ISBN: (纸本)9780863419102

This paper considers the problem of manoeuvring target tracking with bearings-only measurements collected by a single source. We use the switching multiple models description where the target motion is described by a finite collection of m models, each of one corresponding to a possible evolution, and a Markov chain to model the jump between the different models. We test a new approximation scheme to avoid the exponential growth in the number of terms corresponding to the optimal filter.

关键词： Bearings-only TMA Manoeuvring target Hybrid filtering Gaussian mixture hybrid filtering Markov chain targets Gauss optimal filters Exponential Growth Maneuvering

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Intelligent fuel-flow monitoring based on Particle-tracking Velocimetry

Intelligent fuel-flow monitoring based on Particle-Tracking ...

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2008 iet seminar on target tracking and data fusion: algorithms and applications

作者： S. Ingram M. A. Hossain K. P. Dahl Goodrich Engine Control Systems York Road Hall Green Birmingham B28 8LN UK School of Informatics Bradford University B07 1D7 UK

Artificial Neural-Networks have been widely applied in various aspects of Particle—tracking Velocimetry. This paper presents an overview of the different applications and gives an insight into how this technology can be applied to fuel-flow monitoring. The paper presents a methods of flow-field estimation based on Particle-tracking Velocimetry, without the need to solve the correspondence problem. We also present a method of defeating the obscuration problem found in many optical velocimetry schemes.

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Investigation into the utility of using CFAR cluster size information in target track association

Investigation into the utility of using CFAR cluster size in...

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2008 iet seminar on target tracking and data fusion: algorithms and applications

作者： E. J. Hughes I. Izzawati The Institution ofEngineering and Technology Cranfield University Stevenage Hertfordshire UK

ISBN: (纸本)9780863419102

During CFAR processing of low-resolution-radar data (e.g. from yacht navigation systems), the target is represented by a cluster of range-azimuth cells. The centroid is usually passed to the tracking system, however information on the size of the cluster, and therefore extent of location error is available from the CFAR. The main hypothesis of this paper is "would the use of the cluster bounding-box 'corners' allow better plot-to-track associations when compared to using the region centroid alone?".

关键词： Plot-to-track association Corner Centroid CFAR UKF Radar Centroid corners radar targets location error information Clusters

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A new algorithm for GMTI tracking problems, subject to a Doppler blind zone constraint

A new algorithm for GMTI tracking problems, subject to a Dop...

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2008 iet seminar on target tracking and data fusion: algorithms and applications

作者： J. M. C. Clark P. A. Kountouriotis R. B. Vinter The Institution ofEngineering and Technology Printed and published by the lET Imperial College London Stevenage Hertfordshire UK

ISBN: (纸本)9780863419102

This paper introduces a new methodology to take account of the Doppler blind zone arising, for example, in GMTI tracking. Here, the measurements are suppressed, when the range-rate of the target drops below a specified threshold. algorithms based on the new methodology are easy to implement, robust to choice of initial distributions and computationally efficient. Simulations have been conducted for a number of scenarios featuring in earlier comparative exercises. The new techniques exhibit a uniform improvement in estimation accuracy, as compared with earlier proposed approximate analytic techniques.

关键词： target tracking Bayesian methods Minimum detectable velocity Blind Doppler Radar target tracking radar Bayes methods algorithms new technique Dead band A* Algorithm

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A novel algorithm for tracking targets using manoeuvre models

A novel algorithm for tracking targets using manoeuvre model...

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2008 iet seminar on target tracking and data fusion: algorithms and applications

作者： Kevin Gilholm Nick O. Everett QinetiQ Stevenage Hertfordshire UK

ISBN: (纸本)9780863419102

We present a novel algorithm for robust tracking of targets in challenging scenarios by modelling their high level behaviour. The particle-filter [6] based algorithm combines the benefits of variable-rate filtering [5] with a variable- dimension, manoeuvre-based representation of the target trajectory. Variable-rate filtering allows the algorithm to model manoeuvre changes at arbitrary (non-measurement) times, while manoeuvre-based modelling adds to track robustness by providing a parsimonious representation of the target trajectory. The efficiency of the particle filter has been greatly enhanced using reversible-jump Markov Chain Monte Carlo [7] moves that are applied in a Resample-Move fashion [4]. We demonstrate the performance of the algorithm on some example representative scenarios.

关键词： target tracking Particle filters Manoeuvre models Variable-rate filtering Markov Chain Monte Carlo Markov chain monte carlo methods Particle filters target tracking algorithms targets A* Algorithm Modeling

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Multi-platform multi-target tracking fusion via covariance intersection: Using fuzzy optimised modified Kalman Filters with measurement noise covariance estimation

Multi-platform multi-target tracking fusion via covariance i...

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2008 iet seminar on target tracking and data fusion: algorithms and applications

作者： Timothy J. Wren Asher Mahmood General Dynamics Stevenage Hertfordshire UK

ISBN: (纸本)9780863419102

Presented in this paper is a detailed novel approach to tracking multiple moving targets from multiple moving platforms and fusing the individual estimates within platform centric nodes via covariance intersection. The approach presents a method of deconstructing the target model into a nonlinear element and a Kalman filter, modelling the target position and velocity vectors of the targets. The method avoids the increased complexity of using extended Kalman filters. The model state noise covariance is restructured by considering the source of the noise within the simplified imposed model and the measurement noise covariance is estimated from a single coefficient optimized moving average filter. The filter coefficient is optimally determined by the minimization of the variance of the Frobenius norm of the current estimated measurement covariance matrix, via a fuzzy logic feedback structure.

关键词： Fuzzy Kalman Filter Covariance Intersection Covariance Kalman filters Noise Intersection Euclidean matrix norm Noise measurement Filter coefficient nonlinear device fusion reactions fusion, biological fusion fusion (melting) tracking targets

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Projection filters and matched moment filters in tracking

Projection filters and matched moment filters in tracking

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2008 iet seminar on target tracking and data fusion: algorithms and applications

作者： J.M.C. Clark Imperial College London Stevenage Hertfordshire UK

In problems in tracking, the natural stochastic model for the measurements and the dynamics of target and observer often contain nonlinear elements, and the design of a recursive tracking algorithm has to be treated as a problem of approximation in nonlinear filtering. The extended Kalman filter has proved to be a surprisingly effective algorithm, producing good estimates for many problems, but it is susceptible to sudden loss of track. Consequently, as the demands on the performance of tracking algorithms have increased, new methods of tracker design have emerged, notably the particle filter and the unscented Kalman filter of Julier, Uhlman and Durrant-Whyte. These are general methods in nonlinear filter design, that have enabled the class of problems for which there are effective algorithms to be greatly extended. But they, too, have their limitations: the particle filter, though highly flexible, is computationally expensive; the unscented Kalman filter, though it is widely applicable and much more 'robust' than the extended Kalman filter, can still lose accuracy in some extreme *** achieve both computational efficiency and accuracy in tracking appears to require the design of algorithms that are more closely tailored to the problem in hand.

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tracking and identification of agile targets from armoured fighting vehicles

Tracking and identification of agile targets from armoured f...

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2008 iet seminar on target tracking and data fusion: algorithms and applications

作者： Peter Emmett General Dynamics Stevenage Hertfordshire UK

ISBN: (纸本)9780863419102

To deal with asymmetric and adaptive threats, situational awareness and tracking systems require an inbuilt adaptive capability that is quantitatively geared to the dynamics of the human operational context. The physical form of surveillance systems is examined and fixed sensor strategies for situational awareness systems are shown to have significant drawbacks. Steerable sensors lead to a more effective capability that achieves faster identification after first target detection and is able to support smart, adaptive scanning and tracking modes. The design of situational awareness systems is considered from the standpoint of how much information should be presented to the military user at any one time. An analysis of the human operational context is presented, leading to situational adaptation based on novel sensor link budgets, end-to-end from sensor to user.

关键词： Awareness Information Electro-optics Execution Mind-bites Awareness electro-optics Legal Executions situational awareness tracking information Sensors tracking SYSTEM targets SURVEILLANCE SYSTEMS

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tracking multiple targets from a mobile robot platform using a laser range scanner

Tracking multiple targets from a mobile robot platform using...

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2008 iet seminar on target tracking and data fusion: algorithms and applications

作者： Polychronis Kondaxakis Stathis Kasderidis Panos Trahanias Institute of Computer Science Foundation for Research and Technology-Hellas Hella Greece

ISBN: (纸本)9780863419102

A major issue in the field of mobile robotics today is the detection and tracking of moving objects (DATMO) from a moving observer. In dynamic and highly populated environments, this problem presents a complex and computationally demanding task. It can be divided in sub-problems such as robot’s relative motion compensation, feature extraction, measurement clustering, data association and targets’ state vector estimation. In this paper we present an innovative approach that addresses all these issues exploiting various probabilistic and deterministic techniques. The algorithm utilizes real laser-scanner data to dynamically extract moving objects from their background environment, using a time-fading grid map method, and tracks the identified targets employing a Joint Probabilistic data Association with Interacting: Multiple Model (JPDA-IMM) algorithm. The resulting technique presents a computationally efficient approach to already existing target-tracking research for real time application scenarios.

关键词： tracking Mobile Robots DATMO JPDA IMM Mobile robots IMM tracking data association targets LASER RANGING Moving Probability

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Evolving networks for group object motion estimation

Evolving networks for group object motion estimation

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2008 iet seminar on target tracking and data fusion: algorithms and applications

作者： Amadou Gning Lyudmila Mihaylova Simon Maskell Sze Kim Pang Simon Godsill Department of Communication Systems Lancaster University UK Dept. of Communication Systems Lancaster University UK Malvern Technology Centre QinetiQ Worcestershire UK Department of Engineering University of Cambridge UK

ISBN: (纸本)9780863419102

This paper proposes a technique for group object motion estimation based on evolving graph networks. The main novelty over alternative group tracking techniques stems from learning the network structure for the group. An algorithm is proposed for automatic graph structure initialisation, incorporation of new nodes and unexisting nodes removal in parallel with the edge update. This evolving graph model is combined with the sequential Monte Carlo framework and its effectiveness is illustrated over a complex scenario for group motion estimation in urban enviroment. Results with merging, splitting and crossing of the groups are presented with high estimation accuracy.

关键词： Evolving graphs Random graphs Group target tracking Monte Carlo methods Nonlinear estimation nonlinear estimation Monte Carlo technique Graphical models Network merger

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