Abstract
Many sensor network applications require location awareness, but it is often too expensive to equip a global positioning system (GPS) receiver for each network node. Hence, localization schemes for sensor networks typically use a small number of seed nodes that know their locations and protocols whereby other nodes estimate their locations from the messages they receive. For the inherent shortcomings of general particle filter (the sequential Monte Carlo method) this paper introduces particle swarm optimization and weighted centroid algorithm to optimize it. Based on improvement a distributed localization algorithm named WC-IPF (weighted centroid algorithm improved particle filter) has been proposed for localization. In this localization scheme the initial estimate position can be acquired by weighted centroid algorithm. Then the accurate position can be gotten via improved particle filter recursively. The extend simulation results show that the proposed algorithm is efficient for most condition.
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