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 lJ毛compared with AHP, and about 10% with TOPSIS.The proposed model is simple, intuitive, feasible, and its result is more objective, stable, and effective.