A Target Tracking Node Selection Method for UWSNs Based on Dynamic Topology

In order to improve the energy utilization efficiency of underwater wireless sensor networks (UWSNs) in target tracking, a node selection algorithm based on dynamic posterior Cramer-Rao lower bound (PCRLB) is proposed and extended to passive tracking scenarios. First, a residual correction particle filter (RCPF) algorithm is proposed to effectively reduce the interference of complex underwater noise. The RCPF algorithm is validated through simulations and real-world experiments, demonstrating its effectiveness in practical underwater conditions. Next, the mathematical relationship between the node position and the dynamic PCRLB is established. The optimal dynamic PCRLB for the node is then derived using the Lagrange multiplier method and conjugate gradient method. Finally, the node’s optimal dynamic PCRLB and the mobile energy consumption are used as the criteria for node selection. By selecting nodes with better indicators to participate in target tracking, the energy efficiency of target tracking is improved. The simulation results show that the proposed algorithm can effectively improve the energy efficiency of target tracking and prolong the network lifetime, showcasing its practical value in underwater monitoring applications.