A Secure Localization Scheme for UWSNs based on AUV Formation Cooperative Beamforming

In harsh underwater environments, position accuracy and privacy of sensors are equally important. Most underwater localization schemes suffer from privacy leakage, and privacy protection schemes for terrestrial networks are not applicable to underwater acoustic networks with stratification effects and multipath. Therefore, this paper proposes a secure localization scheme based on autonomous underwater vehicle (AUV) formation cooperative beamforming for underwater wire-less sensor networks (UWSNs) considering acoustic channel char-acteristic. The underwater sensor receives position information from multiple AUV anchors and utilizes time difference of arrival (TDOA) for self-localization. Eavesdroppers exist to overhear the information emitted by the anchors, thereby destroying the entire localization system. We model the secure localization requirement as a multi-AUV multi-objective dual joint optimization problem to optimize the security and energy performance, and adopt the deep reinforcement learning (DRL)-based multi-agent deep deterministic policy gradient (MADDPG) algorithm to solve it. Simulation and sea experimental results corroborate the efficiency and accuracy of the proposed secure localization scheme.