LAUSR

Localization is an essential service for numerous applications in wireless ad hoc networks. In particular, cooperative localization is a widely used technique for improving performance by utilizing information obtained from adjacent sensors. In general, distributed localization in ad hoc networks shows relatively low performance compared to centralized localization. This is partly due to the lack of information and partly because of error propagation. In this article, we propose a localization algorithm considering the location uncertainty of reference nodes. The proposed algorithm uses a dilution of precision, depending on the geometric deployment of reference nodes, as a representative value of uncertainty. The proposed algorithm estimates the position of a target node and re-estimates positions of reference nodes concurrently. Using the proposed algorithm, we can reduce the effect of accumulated error propagation and enhance the accuracy of estimated node positions. We verify the feasibility of the proposed algorithm and compare its performance with that of other localization schemes under several circumstances by performing simulations. The results show that the overall performance of the proposed algorithm outperformed that of other schemes.