Hierarchical detection and tracking for moving targets in underwater wireless sensor networks

Abstract

It is difficult to improve both energy consumption and detection accuracy simultaneously, and even to obtain the trade-off between them, when detecting and tracking moving targets, especially for Underwater Wireless Sensor Networks (UWSNs). To this end, this paper investigates the relationship between the Degree of Target Change (DoTC) and the detection period, as well as the impact of individual nodes. A Hierarchical Detection and Tracking Approach (HDTA) is proposed. Firstly, the network detection period is determined according to DoTC, which reflects the variation of target motion. Secondly, during the network detection period, each detection node calculates its own node detection period based on the detection mutual information. Taking DoTC as pheromone, an ant colony algorithm is proposed to adaptively adjust the network detection period. The simulation results show that the proposed HDTA with the optimizations of network level and node level significantly improves the detection accuracy by 25% and the network energy consumption by 10% simultaneously, compared to the traditional adaptive period detection schemes.