A Multi-Node Cooperative Bearing-Only Target Passive Tracking Algorithm via UWSNs

Abstract

Underwater target passive tracking has ubiquitous applications in oceanic fields for both commercial and military purposes. The underwater wireless sensor networks (UWSNs) draw great interest and become promising tools for underwater target passive tracking. However, batteries provide power for nodes in the UWSNs, and it is unrealistic to replace them when their energies are exhausted. Therefore, it is essential to study on energy-efficient underwater target passive tracking algorithm. To make a tradeoff between tracking accuracy and energy consumption, this paper proposes a multi-sensor cooperative bearing-only passive tracking algorithm based on dynamic clustering via UWSNs. Under the framework of distributed fusion, we utilize the linear minimum variance fusion criterion to minimize the trace of fusion error covariance. Furthermore, we introduce the dynamic clustering process into passive target tracking, select cluster head nodes from the perspective of energy consumption, and choose cluster member nodes through an adaptive node selection method, which formulates the nodes selection problem into a knapsack problem in mathematics. Finally, the simulation results and analysis demonstrate that this algorithm can effectively reduce energy consumption on the premise of sufficient tracking accuracy.