Abstract
Underwater wireless sensor networks (UWSNs) can provide a promising solution for underwater target tracking. Due to the limitation of energy consumption, only a part of nodes are selected to track the target. As we know, most research about node selection for underwater target tracking in UWSNs is carried out under the ideal underwater condition. Actually, the activated sensor nodes may acquire more than one measurement due to clutter. This paper presents a new node selection scheme under measurement origin uncertainty. Firstly, the problem of measurement origin uncertainty is dealt via probabilistic data association filter (PDAF) and the multi-sensor particle filter (PF) under measurement origin uncertainty is designed. Secondly, the relationship between node topology and posterior Cramer-Rao lower bound (PCRLB) is derived to select sensor nodes. Then the node selection scheme is proposed for underwater target tracking under measurement origin uncertainty. Finally, simulation results are presented to verify the effectiveness of our method.
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