水下多目标跟踪系统攻击目标优选模型及算法

攻击目标优选是水下多目标跟踪（MTT）系统的重要组成部分。目标估计值的不精确性使优选具有模糊性，常用的经典决策方法如层次分析（AHP）法和理想解（TOPSIS）法存在精度要求高、结果稳定性差等问题，不适用于水下目标优选。该文以水下MTT系统为研究对象，运用灰色关联优选（GROD）法建立了攻击目标优选模型，解决了水下MTT过程中的目标排序以及由于目标特征值不精确引起的攻击目标误判问题。结合实例介绍了GROD方法在MTT系统中的应用，并借助系统效能分析工具与其他常用经典评估决策方法进行了比较，效能统计结果表明，应用GROD法的系统效能比AHP法提高约15％，比TOPSIS法提高约10％。GROD模型算法简单、直观、合理，计算结果客观、稳定，系统效能高，将其应用于水下MTT系统攻击目标优选评估在技术上是可行的。

Model and Algorithm for Attacked Target Optimization in Underwater Multi-targets Tracing System

Target optimal decision is an important component of the underwater multi-target tracing(MTT)system.Imprecise information of target leads to a fuzzy optimization.The classical methods such as the analytic hierarchy process(AHP)and the technique of order preference by similarity to ideal solution(TOPSIS)require high precision and provide unstable result,so they are not applicable to the system of underwater MTT.A model for attacked target optimization in underwater MTT system was established based on gray relation optimal decision(GROD),to resolve the problems of target optimal decision in the process of underwater MTT and a miscarriage of justice of attacked target because of the imprecise information.An example was utilized to explain the application of GROD in underwater MTT system and compare the system effectiveness of AHP and TOPSIS methods.The results show that the effectiveness of GROD is improved by about 15% compared with AHP,and about 10% with TOPSIS.The proposed model is simple,intuitive,feasible,and its result is more objective,stable,and effective.