A Distributed Localization Algorithm for Wireless Sensor Networks Based on the Solutions of Spatially-Constrained Local Problems

We present a distributed localization algorithm for wireless sensor networks. Each sensor estimates its position by iteratively solving a set of local spatially-constrained programs. The constraints allow sensors to update their positions simultaneously and collaboratively using range and position estimates to those neighbors within their communications range. Moreover, the algorithm is designed for implementation with resource-limited devices. Since the exchange of information among sensors is a key component for this method, we introduce a stopping criterion to monitor the wireless transmissions for the whole network in order to significantly reduce energy consumption with minimal impact on localization accuracy. Experimental results show that we can determine the best tradeoff between wireless transmissions and accuracy. The performance of the proposed scheme is very competitive when compared with similar and more computationally demanding schemes.