Evasive Maneuver Strategy for UCAV in Beyond-Visual-Range Air Combat Based on Hierarchical Multi-Objective Evolutionary Algorithm

Zhen Yang,Deyun Zhou,Qian Pan,Weiren Kong,Haiyin Piao,Kai Zhang

doi:10.1109/access.2020.2978883

Abstract

This study deals with the autonomous evasive maneuver strategy of unmanned combat air vehicle (UCAV), which is threatened by a high-performance beyond-visual-range (BVR) air-to-air missile (AAM). Considering tactical demands of achieving self-conflicting evasive objectives in actual air combat, including higher miss distance, less energy consumption and longer guidance support time, the evasive maneuver problem in BVR air combat is defined and reformulated into a multi-objective optimization problem. Effective maneuvers of UCAV used in different evasion phases are modeled in three-dimensional space. Then the three-level decision space structure is established according to qualitative evasive tactical planning. A hierarchical multi-objective evolutionary algorithm (HMOEA) is designed to find the approximate Pareto-optimal solutions of the problem. The approach combines qualitative tactical experience and quantitative maneuver decision optimization method effectively. Simulations are used to demonstrate the feasibility and effectiveness of the approach. The results show that the obtained set of decision variables constitutes nondominated solutions, which can meet different evasive tactical requirements of UCAV while ensuring successful evasion.

Highlights

With the rapid development of artificial intelligence technology and its in-depth application in the military field, the combat mission of unmanned combat air vehicle (UCAV) has gradually expanded from the current airborne intelligence, surveillance & reconnaissance [1], close air support, and electronic support measure to the field of air combat
The three-level decision space structure is established according to qualitative evasive tactical planning, which includes timing, type, and parameters of evasive maneuvers
WORK Ensuring tactical superiority and survival probability in BVR air combat are critical to UCAV

Summary

INTRODUCTION

With the rapid development of artificial intelligence technology and its in-depth application in the military field, the combat mission of unmanned combat air vehicle (UCAV) has gradually expanded from the current airborne intelligence, surveillance & reconnaissance [1], close air support, and electronic support measure to the field of air combat. Yang et al.: Evasive Maneuver Strategy for UCAV in Beyond-Visual-Range Air Combat Many approaches, such as differential games [3]–[6], optimum control [7]–[11], model predictive control [12]–[15], and evolutionary algorithms [16]–[21], have been applied to obtain the optimal or approximate optimal evasive maneuver command for a fighter. The above approaches have achieved satisfactory evasion effects in this situation, but they are not fully applicable to evade BVR AAM, which often lanches as the opponent is far from the GKZ The latter studies focus more on recommending to the fighter how to apply tactical planning rather than dynamic advantages.

PROBLEM FORMULATION

NORMALIZED DECOMPOSITION MECHANISM

1) CODING METHOD

SIMULATION AND ANALYSIS

CONCLUSION AND FUTURE WORK