关键词: 威胁评估, 防空作战, 自适应杂交粒子群优化, 最小二乘支持向量机

Abstract: The key link of air defense command and control system is to evaluate the threat degree of air target according to target situation information, the accuracy of the assessment will have a significant impact on air defense operations. Aiming at the shortcomings of traditional evaluation methods, such as poor real-time performance, heavy workload, low evaluation accuracy, and unable to evaluate multiple objectives simultaneously, a method of air target threat assessment based on Adaptive Crossbreeding Particle Swarm Optimization (ACPSO) and Least Squares Support Vector Machine (LSSVM) was proposed. Firstly, according to the air target situation information, the framework of threat assessment system was constructed. Then, ACPSO algorithm was used to optimize the regularization parameter and kernel function parameter in LSSVM. In order to overcome the disadvantages of the traditional crossbreeding mechanism, an improved cross-hybridization mechanism was proposed, and the crossbreeding probability was adjusted adaptively. Finally, the training and evaluation results of the systems were compared and analyzed, and the multi-target real-time dynamic threat assessment was realized by the optimized system. Simulation results show that the proposed method has the advantages of high accuracy and short time required, and can be used to evaluate multiple targets simultaneously. It provides an effective solution to evaluate the threat of air targets.

Key words: threat assessment, air defense operation, Adaptive Crossbreeding Particle Swarm Optimization (ACPSO), Least Squares Support Vector Machine (LSSVM)