Abstract
In an effort to maximize the combat effectiveness of multimissile groups, this paper proposes an adaptive simulated annealing–particle swarm optimization (SA-PSO) algorithm to enhance the design parameters of multimissile formations based on the concept of missile cooperative engagement. Firstly, considering actual battlefield circumstances, we establish an effectiveness evaluation index system for the cooperative engagement of missile formations based on the analytic hierarchy process (AHP). In doing so, we adopt a partial triangular fuzzy number method based on authoritative assessments by experts to ascertain the weight of each index. Then, considering given constraints on missile performance, by selecting the relative distances and angles of the leader and follower missiles as formation parameters, we design a fitness function corresponding to the established index system. Finally, we introduce an adaptive capability into the traditional particle swarm optimization (PSO) algorithm and propose an adaptive SA-PSO algorithm based on the simulated annealing (SA) algorithm to calculate the optimal formation parameters. A simulation example is presented for the scenario of optimizing the formation parameters of three missiles, and comparative experiments conducted with the traditional and adaptive PSO algorithms are reported. The simulation results indicate that the proposed adaptive SA-PSO algorithm converges faster than both the traditional and adaptive PSO algorithms and can quickly and effectively solve the multimissile formation optimization problem while ensuring that the optimized formation satisfies the given performance constraints.
Highlights
Cooperative engagement in multimissile formations is an important means of warfare adapted to future combat environments
To address the issues of the intense infrared radiation produced during missile launch, the poor continuous combat capability of a missile system, the severe ablation of the launcher, and environmental pollution, refs. [10,11] established an improved effectiveness evaluation model based on game theory and analogue-to-digital converters (ADCs) methods
In [13], a combat effectiveness evaluation model based on a Levenberg–Marquardt backpropagation (LMBP) neural network was proposed based on the operating characteristics of antiaircraft missile warheads
Summary
Cooperative engagement in multimissile formations is an important means of warfare adapted to future combat environments. To address the abovementioned issues, this paper addresses the problem of optimal formation design considering the needs of different missions to reduce the energy consumed by a formation’s adjustments in response to continually changing mission requirements during the process of cooperative missile group engagement. In view of the diversity of possible mission requirements during cooperative operations, we develop an optimal multimissile formation design method that satisfies the following conditions simultaneously: it can take into account the needs of different mission requirements; fully and accurately perceive the current battlefield situation; endow a missile group with a greatly enhanced ability to damage the target; effectively improve the missile group’s stealth, manoeuvrability and other penetration capabilities; and ensure that the group can adopt good formations with robust performance. Where Λ represents the group formation and Followeri denotes the positional par5aomf 1e5ters of the i-th follower missile relative to the leader missile
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