Abstract: Packet collisions and signal noises may corrupt ranging packets, resulting in distance measurements data missing and degrading localization performance. A packet corruption tolerant localization algorithm is proposed to address this challenge. First, an energy-efficient mechanism is designed to gather inter-node distance measurements and form partially observed square distance matrix (SDM). Then, leveraging the intrinsic low-rank structure of SDM, the reconstruction of true SDM is formulated as a regularized low-rank matrix factorization problem and an improved Newton-Raphson method is designed to optimize the problem. Finally, a multi-dimension scaling technique is applied to localize all the nodes based on the reconstructed SDM. Simulation results demonstrate that the proposed algorithm outperforms the benchmark approaches in terms of localization accuracy, coverage and stability.

Key words: underwater acoustic sensor networks, packet corruption tolerant localization, low-rank matrix factorization, multi-dimensional scaling