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This paper addresses collaborative target tracking in wireless sensor networks where the probabilistic sensing model is adopted because disk sensing model is coarse and unrealistic. However, the probabilistic sensing model will lead to the decrease of useful sensor nodes, the degradation of detection probability, and the divergent of tracking results. To address those problems, mobile sensor nodes are adopted and a novel sensor management strategy with mobile sensor nodes is proposed based on the distributed Kalman filtering fusion with feedback. Simulation results verify that the number of useful sensors, the collaborative detection probability and the tracking performance are obviously improved.
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