A Relative Positioning Technique with Spatial Constraints for Multiple Targets Based on Sparse Wireless Sensor Network

Many applications of wireless sensor network require precise knowledge of the locations of nodes. Conventional sparse wireless sensor network, which is formed by a restricted number of nodes, has two drawbacks, i.e., low connective ratio and hop count limited, which probably cause the network link failure and/or low locating performance. To improve the relative position precision and reliability of multiple targets based on the sparse wireless sensor network, a relative locating method with spatial constraints is proposed according to the different network configuration and inter-range between target nodes for the sparse wireless sensor network, of which the spatial constraint benchmarks include two categories of datum, namely, the spatial absolute displacement datum and direction rotation datum. In particular, it is proven on the basis of the principle of survey adjustment that the nodes’ position ambiguity, which is caused by the rank deficiency, could be solved while the estimating precision of the target nodes position is unchanged. The simulation results show that compared to the conventional time-varying filtering, e.g. Kalman Filtering, the proposed constraint position method may rapidly respond to network-link communication failure, and increase relative positioning precision about 32.9 % via introducing the spatial constraint benchmarks. Copyright © 2013 IFSA.