Bias self-adaptive correction-based localization algorithm for underwater wireless sensor networks

This paper proposes a novel multi-hop localization algorithm based on bias self-adaptive correction to solve the distance estimation bias problem for underwater wireless sensor networks (UWSNs), which are commonly deployed in complex ocean environments. The principle of our scheme is firstly to exclude the poor anchors with location bias so as to establish the reliable localization sets for the ordinary nodes, and then to use the bias self-adaptive correction approach to enhance the accuracy of multi-hop distance estimation under multiple uncertainties. On this basis, the ordinary nodes performed high-precision coordinates estimation. Simulation results show that our method is capable of eliminating the influence of multiple uncertainties and outperforming the conventional approaches with higher localization accuracy.