Combat Effectiveness Evaluation of Air Defense Missile Weapon System Based on RBF Neural Network

doi:10.16182/j.issn1004731x.joss.23-1571

Abstract

Abstract:

A combat effectiveness evaluation method based on RBF neural network is proposed to address the problems of high dimensionality, high complexity, and subjective evaluation methods in current air defense missile weapon systems. A combat effectiveness index system for air defense missile weapon systems has been constructed by analyzing the OODA environmental combat theory. The RBF neural network model simulation is implemented using MATLAB, and several methods such as BP, PCA-BP, and Elman neural network are compared and verified through simulation. The simulation results show that the predicted evaluation results of the RBF neural network model are closer to the actual values, fully proving the effectiveness of the model in evaluating the combat effectiveness of air defense missile weapon systems and providing strong support to commanders in making operational decisions.

Key words: RBF neural network, air defense missile weapon system, efficiency evaluation, combat simulation, OODA ring

CLC Number:

TP391

Zhang Peng, Feng Ke, Gong Jiancheng, Yang Xiaoqiang, Shen Jinxing. Combat Effectiveness Evaluation of Air Defense Missile Weapon System Based on RBF Neural Network[J]. Journal of System Simulation, 2025, 37(2): 529-540.

Figures/Tables 14

Fig. 1

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Table 1

Partial performance parameters table of air defense missile weapon system

性能指标	序号
性能指标	4	51	126	220	239	400	467	593
雷达发现概率	0.978	0.539	0.213	0.271	0.406	0.779	0.373	0.516
雷达识别概率	0.730	0.881	0.831	0.779	0.795	0.661	0.791	0.709
雷达制导概率	0.910	0.872	0.911	0.782	0.839	0.986	0.808	0.900
最大探测距离	0.985	0.741	0.808	0.936	0.841	0.920	0.736	0.783
地形遮蔽	0.481	0.663	0.473	0.078	0.527	0.744	0.321	0.661
信道容量	0.930	0.616	0.897	0.602	0.850	0.965	1.241	0.967
信息处理延时	0.646	1.146	0.721	0.935	0.945	0.968	0.982	0.827
战场态势评估能力	0.995	0.833	0.809	0.944	0.969	0.983	0.807	0.881
辅助决策能力	0.847	0.829	0.708	0.884	0.656	0.862	0.151	0.377
决策响应时间	1.118	0.692	1.047	0.880	0.459	1.214	0.630	1.071
武器反应时间	0.500	0.856	0.656	0.693	0.952	0.711	0.603	0.083
高界高度	0.990	0.255	0.421	0.898	0.906	0.659	0.203	1.177
近界高度	0.400	0.425	0.253	0.211	1.285	0.173	0.343	0.511
远界斜距	0.991	0.158	0.855	0.550	0.684	0.203	0.427	1.344
近界斜距	1.667	0.725	0.141	1.590	0.551	1.168	0.368	0.499
最大高低角	0.667	0.756	1.101	0.811	0.578	0.697	0.707	1.026
最大航路角	0.584	0.855	0.763	0.640	1.014	0.538	0.779	0.700
目标容量	0.162	0.409	0.254	0.503	0.899	0.961	0.587	0.023
发射装置数量	0.500	0.484	0.523	0.590	0.165	0.523	0.429	0.414
导弹联装数	0.800	0.617	0.409	0.501	0.141	0.866	0.888	0.616
单目标射弹数	0.750	0.537	0.515	0.377	0.700	0.616	0.610	0.463
导弹装填时间	0.830	0.755	0.759	0.471	0.698	0.677	0.685	0.834
单发命中率	0.976	0.589	0.973	0.941	0.984	0.867	0.979	0.895
抗干扰能力	0.738	0.910	0.917	0.803	0.876	0.945	0.807	1.006
可用过载	0.700	0.510	0.573	1.062	0.592	0.898	0.889	0.872
发动机工作时间	0.994	0.918	0.953	1.048	0.881	0.884	0.727	0.928
最大速度	0.990	0.442	0.404	0.600	1.097	0.465	0.271	0.270
反侦察能力	0.896	0.885	1.048	1.032	0.841	0.972	0.888	0.969
抗毁能力	0.990	0.621	0.718	0.779	0.838	0.764	1.278	1.024
展开时间	0.794	0.791	1.046	0.826	0.954	0.965	0.790	0.950
撤收时间	0.750	0.705	0.806	0.855	0.821	0.794	0.886	0.843
最大行军速度	0.550	0.482	0.471	0.506	0.558	0.608	0.606	0.550
最大行军里程	0.750	0.898	0.772	0.727	0.624	0.776	0.734	0.666
平均故障间隔时间	0.986	0.654	0.557	0.785	0.710	0.407	0.859	0.474
平均修复时间	0.282	0.348	0.291	0.405	0.986	0.132	0.158	0.557
目标种类	0.800	0.759	0.662	0.703	0.672	0.833	0.769	0.502
目标机动过载	0.650	0.649	0.824	0.533	0.823	0.727	0.926	0.598
目标雷达截面	0.780	0.930	1.083	0.787	0.737	0.797	0.796	1.150
目标最大速度	0.750	0.746	0.859	0.755	0.951	1.140	1.051	0.869
期望值	0.780	1.198	0.796	1.048	0.801	0.986	0.905	0.639

Table 1

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Fig.12

Fig. 13

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