Unmanned Aerial Vehicle Situation Assessment Based on Cumulative Prospect Theory and Three-Way Decision

doi:10.16183/j.cnki.jsjtu.2021.400

Abstract

Abstract:

General uninhabited aerial vehicle (UAV) situation assessment methods do not consider the influence of complex external environment on the decision-maker, and usually only get the ranking results of the evaluation. Since the decision-maker needs to make decisions in a short period of time, misjudgments or missing strike windows often occur. To address this problem, a three-way decision model based on the cumulative prospect theory is proposed. First, the method the utilizes intuitionistic fuzzy technique for order preference by similarity to an ideal solution to estimate the conditional probability of each target and obtains the situation assessment result. Next, the method calculates the intuitionistic fuzzy situation information obtained by the UAV based on the cumulative prospect theory, and obtains the corresponding cumulative prospect value when each target performs different actions. Finally, based on the principle of maximizing the cumulative prospect value, a new three-way decision rule is derived to divide the situational assessment results into three regions. The experimental analysis shows that the method not only obtains the target threat ranking, but also classifies the target threat level objectively. At the same time, it considers the psychology of the decision-maker in the assessment process, and obtains the target threat assessment results that meet the traits of the decision-maker, providing a reasonable decision support for the complex and changing air combat.

Key words: uninhabited aerial vehicle (UAV), three-way decision, cumulative prospect theory, situation assessment, intuitionistic

CLC Number:

V279

LI Weiwei, GAO Peixue, CHEN Jin, LU Yuqing. Unmanned Aerial Vehicle Situation Assessment Based on Cumulative Prospect Theory and Three-Way Decision[J]. Journal of Shanghai Jiao Tong University, 2022, 56(11): 1479-1490.

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动作	C	?C
a_P	λ_PP	λ_PN
a_B	λ_BP	λ_BN
a_N	λ_NP	λ_NN

目标	T₁	T₂	T₃	T₄	T₅
类型	(0.7, 0.2)	(0.7, 0.0)	(0.5, 0.1)	(0.5, 0.3)	(0.1, 0.6)
距离	(0.235, 0.702)	(0.281, 0.662)	(0.194, 0.747)	(0.203, 0.759)	(0.726, 0.232)
角度	(0.446, 0.272)	(0.279, 0.515)	(0.223, 0.511)	(0.248, 0.584)	(0.446, 0.272)
速度	(0.546, 0.193)	(0.136, 0.718)	(0.579, 0.274)	(0.239, 0.637)	(0.568, 0.903)
高度	(0.517, 0.167)	(0.346, 0.501)	(0.041, 0.917)	(0.172, 0.824)	(0.517, 0.286)
干扰能力	(0.5, 0.1)	(0.7, 0.0)	(0.8, 0.1)	(0.2, 0.5)	(0.0, 0.6)
穿透能力	(0.8, 0.1)	(0.3, 0.4)	(0.8, 0.0)	(0.3, 0.1)	(0.3, 0.5)
防护能力	(0.6, 0.3)	(0.6, 0.1)	(0.8, 0.1)	(0.6, 0.3)	(0.2, 0.7)

目标	P_r(C\|T_i) (σ=0.35)
T₁	0.7431
T₂	0.5411
T₃	0.6208
T₄	0.3409
T₅	0.3070

权重类型	T₁	T₂	T₃	T₄	T₅
w⁺(P_r(C\|T_i)	0.5633	0.4420	0.4856	0.3399	0.3221
w^-(P_r(C\|T_i)	0.6209	0.4799	0.5320	0.3542	0.3322
w⁺(P_r(?C\|T_i)	0.2947	0.3997	0.3595	0.5081	0.5293
w^-(P_r(?C\|T_i)	0.2983	0.4283	0.3786	0.5583	0.5826

目标	动作	σ=0.35
目标	动作	C	?C
T₁	a_P	0.2610	-0.4570
	a_B	-0.2610	-0.1600
	a_N	-0.7548	0.1600
T₂	a_P	0.2233	-0.5823
	a_B	-0.2233	-0.2038
	a_N	-0.6380	0.2038
T₃	a_P	0.2297	-0.5079
	a_B	-0.2297	-0.1778
	a_N	-0.6564	0.1778
T₄	a_P	0.1748	-0.6923
	a_B	-0.1748	-0.2423
	a_N	-0.4995	0.2423
T₅	a_P	0.1709	-0.7054
	a_B	-0.1709	-0.2469
	a_N	-0.4884	0.2469