A Dynamic Evaluation Method for Collaborative Search Efficiency of Multi-Sonar Systems Under Uncertain Situations
Shizhe Wang, Weiyi Chen, Zongji Li, Xu Chen · Applied Sciences · 2025
In sonar collaborative search tasks, effectively evaluating the collaborative search efficiency is an important way to measure whether a task can be successful, which can also provide strong support for optimizing search schemes. In complex marine environments, sonar collaboration search faces challenges such as uncertain task scenes and real-time changing situations. Traditional evaluation methods cannot meet the evaluation requirements in these tasks since they do not analyze the involved dynamic modeling process. To bridge this gap, in this paper, we propose a novel evaluation method for sonar collaborative search efficiency based on adaptive information fusion and dynamic deduction. Specifically, we develop an information fusion method for multi-sensor detection based on adaptive weight calculation first, weights are assigned to each sensor based on the real-time changing detection probability to obtain more accurate detection probability fusion results. Then, we introduce the Monte Carlo sampling concept to establish an efficiency evaluation model based on the information fusion results. It discretizes the sonar search path and target motion trajectory in the time and space, and calculates the sonar detection efficiency point by point, which can overcome the challenge of uncertain situation conditions due to the uncertainty of target motion by dynamic spatial-temporal deduction. Compared with the average weighted fusion method, the variance of the proposed adaptive fusion method decreases from 0.01 to 0.0071, which proves its better stability. The results of the one-sample t-test indicate that at the level of α=0.05, there is a significant difference between the average detection probability and the random probability of 0.5, indicating statistical significance. Moreover, we verify the effectiveness of the proposed method in fully-passive and multi-base working modes, and compare the impact of each sonar on the overall detection capability of the multi-sonar system, which also demonstrates the advantages and reliability of the new model.