PROMETHEE-Based Multi-AUV Threat Assessment Method Using Combinational Weights

Abstract

The assessment of multiple incoming autonomous underwater vehicles (multi-AUVs) and threat prioritization are critical to underwater defense. To solve problems troubling multi-AUV threat assessment solutions, such as difficult data analysis, high subjectivity, and rigid prioritization logic, we propose the PROMETHEE algorithm based on fusion weights calculated twice by entropy and an analytic network process (ANP), respectively. First, according to AUV detection performance and underwater confrontation situation analysis, the main criteria and indicators of threat assessment are determined. The threat assessment system is provided by unified measurement of these indicators. Then, through analysis and assessment, the weighting algorithm is designed using entropy and ANP. The subjective weight calculated based on ANP and the objective weight obtained based on the entropy method are fused twice to obtain the combined weights, and the influence of subjective and objective factors on problem analysis is considered. Finally, by analyzing the simulation results of a multi-AUV, it is proven that the proposed algorithm is scientific and effective for AUV threat assessment. According to the experimental results, accurate evaluation of the target improved by at least 10%, enabling delivery of results close to the real confrontation situation with high reliability.