Combination search strategy‐based improved particle swarm optimisation for resource allocation of multiple jammers for jamming netted radar system

Abstract

This paper presents a new algorithm named combination search strategy (CSS)‐based improved particle swarm optimisation (IPSO) to address the resource allocation problem of multiple jammers. First, the authors propose a CSS to effectively broaden the limited search range of the two‐step solving framework. This method not only simplifies the solution framework but also considers the combined relationship between beam pointing and transmit power to determine the global solution to the original problem directly. Second, the authors propose the IPSO because the complexity of the decision variables is increased by CSS. This method can change the focus of searching the optimal solution at different stages, correct the direction of particle evolution over time and avoid the interference between the variables. Finally, this study simulates the problem of resource allocation of multiple jammers based on the CSS‐IPSO. Based on the simulation results, the combined search strategy can obtain better resource allocation results in a short time, and the IPSO algorithm can further improve the accuracy and stability of the resource allocation results.

Cooperative Jamming Resource Allocation with Joint Multi-Domain Information Using Evolutionary Reinforcement Learning

“…Numerous scholars have conducted research on the problem of cooperative jamming resource allocation for multiple jammers. Zou [23], Wu [24], Jiang [25], and others have made improvements to the PSO algorithm to enhance its optimization probability and stability when dealing with cooperative jamming resource allocation. Lu et al [26] employed detection and targeting probability to characterize the jamming effectiveness of a networked radar system in search and tracking modes, constructed a dual-factor jamming effectiveness assessment function, established a non-convex optimization model for cooperative jamming in a networked radar system, and utilized the dynamic adaptive discrete cuckoo search algorithm (DADCS), featuring improved path update strategies and the introduction of a global learning mechanism, to solve the model.…”