Nondominated Maneuver Strategy Set With Tactical Requirements for a Fighter Against Missiles in a Dogfight

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 multiobjective 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.

A Coordinated Air Defense Learning System Based on Immunized Classifier Systems

“…Several algorithms and approaches have been applied to realize control systems that enable autonomous systems to execute complex missions [29][30][31][32][33][34][35]. For instance, an autonomous decision-making for unmanned combat aerial vehicles (UCAVs) using genetic fuzzy trees is presented by authors in [29].…”

“…A multi-agent-based training system for USVs was presented in [35] and a combat task for combat USVs was used to evaluate the system performance. Other methods such as optimizations and game theoretic approaches have been reported [31][32][33].…”

Cooperative Multiple Task Assignment Problem With Target Precedence Constraints Using a Waitable Path Coordination and Modified Genetic Algorithm

“…In the TCSG, there is a target precedence constraint between targets T 1 and T 2 , and then vertex 1 vertex 4 vertex 2 vertex 7 vertex 3 vertex 8, such that edges (1, 4), (4, 2), (2, 7), (7,3), and (3, 8) are defined. Note that target T 3 must be subjected to a simultaneous attack, and then vertex 9 vertex 5 vertex 6 and vertex 9 vertex 10 vertex 6, such that edges (9, 5), (5,6), and (9, 10), (10, 6) are defined. Finally, the TPG was obtained by merging the TESG and TCSG.…”

A Novel Heterogeneous Sensor-Weapon-Target Cooperative Assignment for Ground-to-Air Defense by Efficient Evolutionary Approaches

“…The weight of interception probability β ∆S = 0.5, β ∆Tgo = βq = 0.25. The performance parameters of close-range and medium-range weapon are respectively set as our previous work [35] and [36]. In each salvo, The state transition of target follows the Bernoulli distribution about the interception probability [37], which can be calculated by Equation (19).…”

“…In each salvo, The state transition of target follows the Bernoulli distribution about the interception probability [37], which can be calculated by Equation (19). The performance parameters of the fighter target are also set as [35]: where |S| is the number of the platforms with only close-range weapons; the delayed time parameter t m = 30s. Based on the above initial setting, the following two cases are randomly generated to research the DS/HWTA problem with different sizes and situations.…”