Received June 14, 2020, accepted June 22, 2020, date of publication June 25, 2020, date of current version July 6, 2020. Digital Object Identifier 10.1109/ACCESS.2020.3004864 Nondominated Maneuver Strategy Set With Tactical Requirements for a Fighter Against Missiles in a Dogfight ZHEN YANG , DEYUN ZHOU , WEIREN KONG , HAIYIN PIAO , KAI ZHANG , AND YIYANG ZHAO School of Electronics and Information, Northwestern Polytechnical University, Xi’an 710072, China Corresponding author: Zhen Yang (nwpuyz@foxmail.com) This work was supported in part by the National Natural Science Foundation of China under Grant 61603299 and Grant 61612385, and in part by the Fundamental Research Funds for the Central Universities under Grant 3102019ZX016. ABSTRACT Dogfight is often a continuous and multi-round process with missile attacks. If the fighter only considers the security when evading the incoming missile, it will easily lose the superiority in subsequent air combat. Therefore, it is necessary to maintain as much tactical superiority as possible while ensuring a successful evasion. The amalgamative tactical requirements of achieving multiple evasive objectives in a dogfight are taken into account in this paper. A method of generating a nondominated maneuver strategy set for evading missiles with tactical requirements is proposed. The tactical requirements include higher miss distance, less energy consumption, and higher terminal superiority. Then the evasion problem is defined and reformulated into a multi-objective optimization problem, which is solved by a redesigned multi- objective evolutionary algorithm based on decomposition (MOEA/D). Simulations are used to demonstrate the feasibility and effectiveness of the approach. A set of approximate Pareto-optimal solutions satisfying the tactical requirements are obtained. These solutions can not only guide the fighter to avoid being hit but also achieve the goal of relatively reducing energy consumption and improving terminal superiority. INDEX TERMS Dogfight, decision-making, evasive maneuvers, multi-objective evolutionary algorithm, tactical requirements. I. INTRODUCTION The core of operational idea in air combat is ‘‘Shoot down the opponent and protect yourself’’. With the extensive equip- ment and application of advanced air-to-air missiles (AAM), fighters are facing the increasing threat of high-precision AAM. How to minimize the lethality of enemy AAM through evasive maneuvers is an essential skill for the fighter in a modern dogfight. Besides, active and passive jamming [1], even defending missiles [2] are usually carried out in this process. This paper only studies the problem of evasive maneuvers, which is of great significance to improve the survival probability of the fighter. The literature on air combat deals with two concepts. The first is ‘‘beyond-visual-range (BVR) air combat’’. It deals with situations in which magnitude and rhythm of maneuvers The associate editor coordinating the review of this manuscript and approving it for publication was Sotirios Goudos . are relatively moderate and the engagement distance is far [3]. That is, BVR air combat emphasizes the distance game and the key of evasive maneuvers in these situations is tactical planning. The second is ‘‘dogfight’’, in which the main fea- tures are relatively close distance, high-dynamic, and intense confrontation [4]. There is more of an emphasis on the game of space angle. Therefore, a fighter against missiles in a dogfight should use its dynamic advantage over that of the missile to perform a successful evasion rather than planned strategy [5], [6]. To complete various air combat missions, survivability of the fighter is the basis and prerequisite. Corresponding to the long-term research on the precision guidance capability of missiles [7], the decision of evasive maneuvers of the fighter against missiles in a dogfight has also received widespread attention. Some common approaches such as numerical simulation [8]–[12], optimum control [13]–[17], differential games [18]–[21], and intelligent algorithms [22]–[25] have 117298 This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/ VOLUME 8, 2020