Data association is one of the essential parts of a multiple-target- tracking system. The paper introduces a report-track association-evaluation technique based on the well known Markov-chain Monte-Carlo (MCMC) method...
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Data association is one of the essential parts of a multiple-target- tracking system. The paper introduces a report-track association-evaluation technique based on the well known Markov-chain Monte-Carlo (MCMC) method, which estimates the statistics of a random variable by way of efficiently sampling the data space. An important feature of this new association-evaluation algorithm is that it can approximate the marginal association probability with scalable accuracy as a function of computational resource available. The algorithm is tested within the framework of a joint probabilistic data association (JPDA). The result is compared with JPDA tracking with Fitzgerald's simple JPDA data-association algorithm. As expected, the performance of the new MCMC-based algorithm is superior to that of the old algorithm. In general, the new approach can also be applied to other trackingalgorithms as well as other fields where association of evidence is involved.
This paper describes the continuing development of an image processing system for use on high-speed passenger ferries. The system automatically identifies objects in a maritime scene and uses the detected motion to al...
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This paper describes the continuing development of an image processing system for use on high-speed passenger ferries. The system automatically identifies objects in a maritime scene and uses the detected motion to alert a human observer to potential collision situations. Three integrated image-processing algorithms, namely an image pre-processor, a motion cue generator, and a target tracker, perform the identification and tracking of maritime objects. The pre-processing filters the image and applies a histogram technique to segment the sea from potential objects of interest. The segmented image is passed to the motion cue generator, which provides motion cues based on the differences between consecutive frames of segmented image data. The target tracker applies dynamic constraints on object motion to solve the correspondence problem, thus increasing the confidence that an identified object is a target. Identified and tracked objects are highlighted to a human observer using a white box viewing cue placed directly around the object of interest.
A particle filter approach is suggested for trackingtargets in the presence of spurious measurements that are exhibit an unknown bias relative to the true target location. The filter is demonstrated for the tracking ...
A particle filter approach is suggested for trackingtargets in the presence of spurious measurements that are exhibit an unknown bias relative to the true target location. The filter is demonstrated for the tracking in the presence of possible wake corruption - i.e. sensor measurements may be "captured" by a wake behind the target.
The paper examines the accuracy of the Bar-Shalom formula for computing the fused estimate from two filters, tracking a single target with the exact minimum mean square estimator. It is shown that the errors are small...
The paper examines the accuracy of the Bar-Shalom formula for computing the fused estimate from two filters, tracking a single target with the exact minimum mean square estimator. It is shown that the errors are small and that the simplicity of the Bar-Shalom formula makes it appropriate to use. Simulation results on its use for fusing estimates from two and three filters are presented.
As existing hydrocarbon reservoirs are developed and exploited, the need to improve techniques for identifying new reservoirs and describing existing reservoirs grows. Indeed, it has been reported that unless a step c...
As existing hydrocarbon reservoirs are developed and exploited, the need to improve techniques for identifying new reservoirs and describing existing reservoirs grows. Indeed, it has been reported that unless a step change in resolution is achieved, production from the North Sea fields will start to decline mid decade. This paper explores the potential for tracking techniques to achieve that step change.
This paper discusses the advantages, disadvantages and methodology of maximum likelihood estimators (MLEs) applied to tracking problems. The paper goes on to explain how a criterion derived by Akaike can, in conjuncti...
This paper discusses the advantages, disadvantages and methodology of maximum likelihood estimators (MLEs) applied to tracking problems. The paper goes on to explain how a criterion derived by Akaike can, in conjunction with the maximum likelihood fit, be used to help optimise the size of the vector of unknown parameters representing the target kinematics. Some of the concepts discussed are illustrated with numerical results relating to a simple bearings-only passive tracking problem.
In this paper, we present notable recent developments in the management of multi-sensor systems, established by the Pattern and Information Processing (PIP) group at QinetiQ Ltd. We describe a generic methodology for ...
In this paper, we present notable recent developments in the management of multi-sensor systems, established by the Pattern and Information Processing (PIP) group at QinetiQ Ltd. We describe a generic methodology for the management of multi-sensor systems in targettracking and present advances in associated implementation within four key application domains. These are: sonobuoy deployment in anti-submarine warfare, fast-jet flight-path optimisation, ground moving target indicator (GMTI) tracking of road-based vehicles, and electronic support measures (ESM) search and track.
The paper addresses the multi-targettracking problem for maneuvering targets in cluttered environments. The multiple scan joint probabilistic data association (MJPDA) algorithm is used for the sake of overcoming the ...
The paper addresses the multi-targettracking problem for maneuvering targets in cluttered environments. The multiple scan joint probabilistic data association (MJPDA) algorithm is used for the sake of overcoming the problem of clutter points and targets which have joint observation. A comparison between different filtering methods through the sliding window of scans is presented. The problem of maneuvering targets is addressed and a new tracking algorithm which uses the multiple scan JPDA and interacting multiple model (IMM) together is formulated.
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