Research on target damage evaluation and optimization algorithm based on random incomplete information

Abstract

Timely and accurate assessment of battlefield strikes can improve the utilization of firepower resources and achieve optimal combat effectiveness. However, due to the complexity and uncertainty of the environment in actual war, it is difficult to obtain accurate target damage information, which can be expressed as uncertain, incomplete, or fuzzy decision information in mathematics. In this paper, the stochastic multi-criteria acceptability analysis method is used to evaluate the damage level of the target under an uncertain environment. We establish a set of characteristic indicators for the target damage effect and use the tracking results of maneuvering targets to determine the degree of target damage. Aiming at the uncertainty of the target data, the upper and lower limit dataset of uncertainty is established, and the membership function of the damage characteristic index is given. Combined with the probability density function, the comprehensive membership function of the damage effect is given, the acceptability index of each damage grade is compared, and the damage effect evaluation with uncertain weight information is given. Based on target vulnerability characteristics and combined with multiple damage elements, a target damage assessment model with multiple damage parameters is established, and the damage results are fitted. We study the relationship between target damage efficiency and various damage parameters. For the optimization strike problem of maximum damage to targets with multiple random incomplete information, a maximum damage optimization model is established using the objective function of maximizing damage probability and the missile firepower coverage area as constraint conditions. Experimental results show that the algorithm used in this paper can effectively solve the damage assessment problem under the condition of random incomplete information.