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Tracking of a moving ground target using acoustic signals obtained from a passive sensor network is a difficult problem as the signals are contaminated by wind noise and are hampered by road conditions, terrain and multipath, etc., and are not deterministic. Multiple target tracking becomes even more challenging, especially when some of the vehicles are light (wheeled) and some are heavy (e.g., tracked...
Target tracking is one of the non trivial applications of wireless sensor network which is set up in the areas of field surveillance, habitat monitoring, indoor buildings, and intruder tracking. Various approaches have been investigated for tracking the targets, considering diverse metrics like scalability, overheads, energy consumption and target tracking accuracy. This paper for the first time contributes...
Collaborative signal processing cluster-based for target tracking in wireless sensor network is proposed in this paper. Node clustering is a useful approach to reduce the communication overhead and develop data fuse in wireless sensor networks. Each sensor node, which has incomplete information about its dynamic and uncertain world, must respond to sensed events within time constraints. The aim of...
For target tracking in Interference Environments of cognitive radar problem, Extended Karman, Particle filter algorithms etc. are generally used to be regarded as usual solutions to state estimation. Many techniques have been developed to improve performance of target tracking. In this paper, we set the structure and key features of target's tracking design for cognitive radar, and newly propose cognitive...
In this paper, the problem of fully-decentralized data fusion is addressed for tracking a target with nonlinear motion model. The problem is solved by applying a fully-decentralized estimation algorithm based on the extended information filter. We propose the neighbor selection and information selection algorithms for sensor selection based on their closeness to the estimated target position and their...
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