Directional Sampling and Refinement Localization Scheme for wireless sensor networks

Location estimation is a fundamental issue for wireless sensor networks (WSNs). In this paper, a directional sampling and refinement localisation scheme for wireless sensor networks is proposed. The algorithm includes two stages. In first stage, sampling is carried out in a directional way, to cover the overlapping area of two anchors´ range, and then the initial position estimate of sensor node comes into being after filtering samples. In second stage, normal node further filters successful samples through collaboration to refine the initial position estimate. This work is based on the following principles: Sampling is carried out in a directional way, to cover the overlapping area of two anchors´ range, thus the probability that the sampling estimate can hit the real position is increased. Simulation results show that the proposed algorithm achieves better accuracy than Sampling Localization and Refinement (SL-R).