Global Sensitivity Analysis on Accuracy of Aviation Fire Control System via DBN Effectiveness Fitting

doi:10.12382/bgxb.2023.0659

Abstract

Abstract:

In view of the fact that most of the current researches on the accuracy of fire control system require high data integrity and only analyze the influence factors of single error source, this paper proposes a novel global sensitivity analysis (GSA) method based on deep belief network (DBN) effectiveness fitting for the accuracy of fire control system. Starting from the advantages and disadvantages of the traditional GSA methods, the limitations of the traditional methods in the case of incomplete data are analyzed. Then, a fire control system performance fitting model is constructed and trained by utilizing the excellent feature extraction ability of DBN and a combination of unsupervised training and supervised fine-tuning methods. The proposed GSADBN method is compared with traditional Sobol method, classical Fourier amplitude sensitivity test (FAST) method and improved BNSobol method. The experimental results show that the proposed GSADBN method can not only meet the accuracy requirements, but also obtain the excellent accuracy analysis results when the data from aviation fire control system is incomplete. Furthermore, GSADBN method can give a reasonable scheme of accuracy value when designing each module of fire control system, so as to provide reference and theoretical support for the design of fire control system and the improvement of combat effectiveness.

Key words: aviation fire control system, deep belief network, GSADBN method, accuracy assessment, global sensitivity analysis

CLC Number:

V19
V233.7

WANG Qianglong, GAO Xiaoguang, LI Xinyu, YAN Xuchen, WAN Kaifang. Global Sensitivity Analysis on Accuracy of Aviation Fire Control System via DBN Effectiveness Fitting[J]. Acta Armamentarii, 2024, 45(10): 3430-3444.

Figures/Tables 16

References 28

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指标类型	参数	数值
	风速/(m·s^-1)	10
	风向角/(°)	30
环境	随机风场风速均方差/(m·s^-1)	3
	随机风场变化周期/s	1
	仿真步长/s	0.1
	仿真最长时间/s	60
	作战飞机高度/m	3000
作战飞机	作战飞机速度/(m·s^-1)	100
	作战飞机偏航角/(°)	15
	作战飞机俯仰角/(°)	0
	目标距离作战飞机距离/m	5000
目标	目标移动速度/(m·s^-1)	20
	目标半径/m	3
武器	武器杀伤半径/m	1

指标类型	参数	数值
	风速/(m·s^-1)	10
	风向角/(°)	30
环境	随机风场风速均方差/(m·s^-1)	3
	随机风场变化周期/s	1
	仿真步长/s	0.1
	仿真最长时间/s	60
	作战飞机高度/m	3000
作战飞机	作战飞机速度/(m·s^-1)	100
	作战飞机偏航角/(°)	15
	作战飞机俯仰角/(°)	0
	目标距离作战飞机距离/m	5000
目标	目标移动速度/(m·s^-1)	20
	目标半径/m	3
武器	武器杀伤半径/m	1

指标类型	参数	参数含义	数值
惯导测	x₁/m	惯导X轴方位测位误差	0~3
位精度	x₂/m	惯导Y轴方位测位误差	0~3
	x₃/m	惯导Z轴方位测位误	0~3
惯导测	x₄/(m·s^-1)	惯导X轴方位测速误差	0~3
速精度	x₅/(m·s^-1)	惯导Y轴方位测速误差	0~3
	x₆/(m·s^-1)	惯导Z轴方位测速误差	0~3
惯导测	x₇/(°)	惯导探测姿态误差	0~0.2
角精度	x₈/(°)	惯导探测俯仰误差	0~0.2
大气数据系统精度	x₉/m	大气机测高误差	20
雷达测距精度	x₁₀/m	雷达探测距离误差	0~3
雷达测	x₁₁/(°)	雷达探测方位角误差	0~0.2
角精度	x₁₂/(°)	雷达探测俯仰角误差	0~0.2

指标类型	参数	参数含义	数值
惯导测	x₁/m	惯导X轴方位测位误差	0~3
位精度	x₂/m	惯导Y轴方位测位误差	0~3
	x₃/m	惯导Z轴方位测位误	0~3
惯导测	x₄/(m·s^-1)	惯导X轴方位测速误差	0~3
速精度	x₅/(m·s^-1)	惯导Y轴方位测速误差	0~3
	x₆/(m·s^-1)	惯导Z轴方位测速误差	0~3
惯导测	x₇/(°)	惯导探测姿态误差	0~0.2
角精度	x₈/(°)	惯导探测俯仰误差	0~0.2
大气数据系统精度	x₉/m	大气机测高误差	20
雷达测距精度	x₁₀/m	雷达探测距离误差	0~3
雷达测	x₁₁/(°)	雷达探测方位角误差	0~0.2
角精度	x₁₂/(°)	雷达探测俯仰角误差	0~0.2

指标	Sobol算法^[13]		BNSobol算法^[15]		GSADBN算法		FAST算法^[10]
指标	主效应值	排序	主效应值	排序	主效应值	排序	主效应值	排序
x₁	0.050	11	0.039	10	0.012	10	0.016	9
x₂	0.055	9	0.043	9	0	11	0.057	3
x₃	0.066	7	0.028	12	0.097	5	0.024	7
x₄	0.168	1	0.055	6	0.368	1	0.509	1
x₅	0.103	4	0.047	8	0.127	2	0.209	2
x₆	0.117	2	0.083	5	0	11	0.052	4
x₇	0.066	7	0.161	1	0.014	9	0.012	11
x₈	0.056	8	0.156	2	0.139	4	0.020	8
x₉	0.116	3	0.036	11	0.170	3	0.011	12
x₁₀	0.077	5	0.049	7	0.024	7	0.050	5
x₁₁	0.051	10	0.155	3	0.021	8	0.025	6
x₁₂	0.076	6	0.146	4	0.027	6	0.015	10