基于改进IFRS相似度和信息熵的反导作战目标威胁评估

doi:10.12305/j.issn.1001-506X.2022.04.20

Abstract

Abstract:

The missile defense target threat assessment method based on improved similarity measure and information entropy of intuitionistic fuzzy rough sets(IFRS) is proposed which conquer the problem of low evaluation accuracy caused by ignoring the hesitancy and weight of target attributes. Firstly, by subdividing the hesitancy of IFRS, the improved IFRS similarity model is proposed, and its properties are proved. Secondly, aiming at the problem that the existing information entropy of IFRS is inconsistent with the intuitionistic fact, the information entropy of IFRS based on cosine function is presented to determine the weight of target attributes. Furthermore, the target threat assessment system is constructed and quantified, and the target threat ranking is achieved by comparing the similarity between the attribute values of the threat targets and the ideal solution. Finally, the simulation example shows the feasibility and effectiveness of the proposed method, which can provide a new attempt for the target threat assessment of missile defense operations in uncertain environment.

Key words: intuitionistic fuzzy rough sets, threat assessment, similarity measure, information entropy

CLC Number:

TP391

Yingqi LU, Chengli FAN, Qiang FU, Xiaowen ZHU, Wei LI. Missile defense target threat assessment based on improved similarity measure and information entropy of IFRS[J]. Systems Engineering and Electronics, 2022, 44(4): 1230-1238.

Figures/Tables 11

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References 30

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IFRS	x₁			x₂
IFRS	赞成	反对	弃权	赞成	反对	弃权
A	4	1	3	5	2	3
B	3	2	3	4	1	3
C	3	0	5	4	1	5

目标层	指标层	指标属性	指标类型
弹道目标威胁评估	距离	定量	成本型
	速度	定量	效益型
	辐射温度	定量	效益型
	RCS	定量	成本型
	极化特性	定性	效益型

威胁度	IFRS	威胁度	IFRS
极大	〈0.85, 0.95, 0.15, 0.05〉	小	〈0.40, 0.50, 0.60, 0.50〉
很大	〈0.80, 0.90, 0.20, 0.10〉	较小	〈0.35, 0.45, 0.65, 0.55〉
较大	〈0.70, 0.80, 0.30, 0.20〉	很小	〈0.20, 0.30, 0.80, 0.70〉
大	〈0.60, 0.70, 0.40, 0.30〉	极小	〈0.10, 0.20, 0.90, 0.80〉
中	〈0.45, 0.60, 0.55, 0.35〉	-	-

目标	目标属性
目标	距离r₁	速度r₂	辐射温度r₃	RCS r₄	极化特性r₅
x₁	〈0.20, 0.30, 0.60, 0.10〉	〈0.30, 0.70, 0.40, 0.20〉	〈0.55, 0.65, 0.40, 0.25〉	〈0.25, 0.60, 0.50, 0.35〉	〈0.70, 0.80, 0.30, 0.20〉
x₂	〈0.30, 0.75, 0.50, 0.25〉	〈0.45, 0.75, 0.30, 0.20〉	〈0.70, 0.85, 0.30, 0.10〉	〈0.50, 0.85, 0.35, 0.10〉	〈0.45, 0.60, 0.55, 0.35〉
x₃	〈0.10, 0.80, 0.65, 0.15〉	〈0.30, 0.65, 0.40, 0.10〉	〈0.45, 0.60, 0.50, 0.25〉	〈0.55, 0.95, 0.25, 0.05〉	〈0.35, 0.45, 0.65, 0.55〉
x₄	〈0.25, 0.85, 0.15, 0.10〉	〈0.20, 0.70, 0.60, 0.30〉	〈0.50, 0.60, 0.45, 0.30〉	〈0.60, 0.80, 0.30, 0.15〉	〈0.80, 0.90, 0.20, 0.10〉
信息熵	0.975 6	0.992 8	0.998 8	0.994 3	0.999 8
属性权重	0.203 4	0.199 8	0.198 7	0.199 6	0.198 5

目标	目标属性
目标	距离r₁	速度r₂	辐射温度r₃	RCS r₄	极化特性r₅
x₁	〈0.040 7, 0.061 0, 0.122 0, 0.020 3〉	〈0.059 9, 0.139 8, 0.079 9, 0.039 9〉	〈0.109 3, 0.129 1, 0.079 5, 0.049 7〉	〈0.049 9, 0.119 7, 0.099 8, 0.069 8〉	〈0.138 9, 0.158 8, 0.059 5, 0.039 7〉
x₂	〈0.061 0, 0.152 5, 0.101 7, 0.050 8〉	〈0.089 9, 0.149 8, 0.059 9, 0.039 9〉	〈0.139 1, 0.168 9, 0.16 8 9, 0.019 8〉	〈0.099 8, 0.169 6, 0.06 9 8, 0.019 9〉	〈0.089 3, 0.119 1, 0.10 9 2, 0.069 5〉
x₃	〈0.020 3, 0.162 7, 0.132 2, 0.030 5〉	〈0.059 9, 0.129 9, 0.079 9, 0.199 9〉	〈0.089 4, 0.119 2, 0.099 3, 0.049 7〉	〈0.109 8, 0.189 6, 0.049 9, 0.099 8〉	〈0.069 5, 0.089 3, 0.129 0, 0.109 2〉
x₄	〈0.050 8, 0.172 9, 0.030 5, 0.020 3〉	〈0.039 9, 0.139 8, 0.119 9, 0.059 9〉	〈0.099 3, 0.119 2, 0.089 4, 0.168 9〉	〈0.119 7, 0.159 7, 0.059 9, 0.029 9〉	〈0.158 8, 0.178 6, 0.039 7, 0.019 8〉

Missile defense target threat assessment based on improved similarity measure and information entropy of IFRS

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方法	目标ζ₁	目标ζ₂	目标ζ₃	目标ζ₄	排序结果	SD_ij/%
文献[16]	0.704 6	0.698 3	0.691 4	0.695 1	1＞2＞4＞3	SD₁₂=0.008 9	SD₂₄=0.004 6	SD₄₃=0.005 3
文献[17]	0.645 2	0.632 6	0.623 9	0.628 8	1＞2＞4＞3	SD₁₂=0.019 5	SD₂₄=0.006 0	SD₄₃=0.007 8
文献[18]	0.830 1	0.820 9	0.811 5	0.815 4	1＞2＞4＞3	SD₁₂=0.011 0	SD₂₄=0.006 7	SD₄₃=0.004 8
文献[19]	0.532 9	0.523 6	0.519 8	0.521 3	1＞2＞4＞3	SD₁₂=0.017 4	SD₂₄=0.004 4	SD₄₃=0.002 9
文献[20]	0.604 6	0.587 4	0.583 2	0.593 6	1>4>2>3	SD₁₄=0.018 2	SD₄₂=0.010 4	SD₂₃=0.007 1
本文算法	0.513 6	0.502 2	0.493 2	0.498 1	1＞2＞4＞3	SD₁₂=0.022 2	SD₂₄=0.008 2	SD₄₃=0.009 8

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