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This paper considers the sensor selection problem for target tracking in large-scale sensor networks. We propose a new sensor selection strategy based on dual-criterion optimization. Both the bias change detection and information gain maximization are considered as criteria in our proposed sensor selection strategy. This new approach extends the sensor selection problem from single criterion optimization...
In the complex pattern classification problem, the fusion of multiple classification results produced by different attributes is able to efficiently improve the accuracy. Evidence theory is good at representing and combining the uncertain information, and it is employed here. Each attribute (set) can be considered as one source of evidence (information). In some applications, the observation of target...
In order for autonomous surface vessels (ASVs) to avoid collisions at sea it is necessary to predict the future trajectories of surrounding vessels. This paper investigate the use of historical automatic identification system (AIS) data to predict such trajectories. The availability of AIS data have steadily increased in the last years as a result of more regulations, together with wider coverage...
Spatial outlier detection in wireless sensor network (WSN) can detect the objects whose non-spatial attributes are significantly different from their spatial neighbors, so as to ensure the reliability and accuracy of sensor data before decision-making process. The main drawback of existing spatial outlier detection algorithms is high user-dependency, which is not suitable for dynamic WSN data. This...
Multi-sensor fusion has been extensively studied i information fusion field, and the distributed target detection i one of the most important applications in the multiple sensor detection theories. In this paper, a data fusion algorithm for target detection is proposed based on tree topology combine with the orderly full binary tree and we discuss the optima threshold fusion rule problem. Different...
A new approach for multi-target tracking under grating lobe environment is presented. Ambiguous angle measurements are obtained by a wide-array antenna whose elements have a long interval. Angle measurements different from the true target angles are obtained because of the grating lobes; therefore, it is difficult to initialize and maintain target tracking accurately. In this paper, we propose a multi-dimensional...
The theory of belief functions is an effective tool to deal with the multiple uncertain information. In recent years, many evidence combination rules have been proposed in this framework, such as the conjunctive rule, the cautious rule, the PCR (Proportional Conflict Redistribution) rules and so on. These rules can be adopted for different types of sources. However, most of these rules are not applicable...
Multiple Object Association (MOA) is an essential process in making vehicles smarter. It consists in associating newly detected objects to previously known ones at each instant in a scene. To treat such matter, the paper proceeds by the use of the Belief Theory introduced by Dempster-Shafer. A crucial concern in this application is the data association complexity and its relative computation time...
Different belief sources often provide conflicting evidence, due to e.g. varying source reliability or deliberate deception. Source trust expresses the source reliability as seen by the analyst. In case of conflicting sources the analyst needs a strategy for managing and revising source trust. Intuitively, trust should be reduced for sources that produce advice which is in conflict with the ground...
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