Multidimensional Comprehensive Evaluation Method for Sonar Detection Efficiency Based on Dynamic Spatiotemporal Interactions

The detection efficiency evaluation of sonars is crucial for optimizing task planning and resource scheduling. The existing static evaluation methods based on single indicators face significant challenges. First, static modeling has difficulty coping with complex scenes where the relative situation changes in real time in the task process. Second, a single evaluation dimension cannot characterize the data distribution characteristics of efficiency indicators. In this paper, we propose a multidimensional detection efficiency evaluation method for sonar search paths based on dynamic spatiotemporal interactions. We develop a dynamic multidimensional evaluation framework. It consists of three parts, namely, spatiotemporal discrete modeling, situational dynamic deduction, and probability-based statistical analysis. This framework can achieve dynamic quantitative expression of the sonar detection efficiency. Specifically, by accurately characterizing the spatiotemporal interaction process between the sonars and targets, we overcome the bottleneck in entire-path detection efficiency evaluation. We introduce a Markov chain model to guide the Monte Carlo sampling; it helps to specify the uncertain situations by constructing a high-fidelity target motion trajectory database. To simulate the actual sensor working state, we add observation error to the sensor, which significantly improves the authenticity of the target’s trajectories. For each discrete time point, the minimum mean square error is used to estimate the sonar detection probability and cumulative detection probability. Based on the above models, we construct the multidimensional sonar detection efficiency evaluation indicator system by implementing a confidence analysis, effective detection rate calculation, and a data volatility quantification analysis. We conducted relevant simulation studies by setting the source level parameter of the target base on the sonar equation. In the simulation, we took two actual sonar search paths as examples and conducted an efficiency evaluation based on multidimensional evaluation indicators, and compared the evaluation results corresponding to the two paths. The simulation results show that in the passive and active working modes of sonar, for the detection probability, the box length of path 2 is reduced by 0∼0.2 and 0∼0.5, respectively, compared to path 1 during the time period from T = 11 to T = 15. For the cumulative detection probability, during the time period from T = 15 to T = 20, the box length of path 2 decreased by 0∼0.1 and 0∼0.2, respectively, compared to path 1, and the variance decreased by 0∼0.02 and 0∼0.03, respectively, compared to path 1. The numerical simulation results show that the data distribution corresponding to path 2 is more concentrated and stable, and its search ability is better than path 1, which reflects the advantages of the proposed multidimensional evaluation method.