Probabilistic localization for outdoor wireless sensor networks

Abstract

Recent advances in wireless communication, low power sensors and microcontrollers enable the deployment of large-scale wireless sensor networks. Localization is a fundamental service required by many wireless sensor network applications. We consider a distributed, probabilistic approach, suitable for outdoor systems with inaccurate range measurements. The approach restricts the possible locations of the nodes by using a combination of positive and negative constraints. We reduce the computational complexity of the algorithm by using two-dimensional fast Fourier transforms (FFTs). We evaluated the proposed probabilistic approach through simulations based on real-world measurements; the results are compared with two other localization schemes and the Cramer-Rao lower bound (CRLB). The results show that, for inaccurate range measurements, the proposed probabilistic approach outperforms existing methods and approaches the CRLB.