Optimal distributed cooperative jamming resource allocation for multi‐missile threat scenario

Abstract

Jamming resources allocation ( JRA) is an essential task in clustered combat environments. Especially in cases with multiple threats, efficient JRA is imperative for protecting key assets. In this study, multiple distributed outboard jammers protecting multiple targets against a multi-missile threat are considered, where the function of JRA includes jamming object selection and jammer power allocation. To address this problem, first, a scheme to evaluate the jamming effectiveness of the radar seeker under cooperative jamming from multiple jammers is proposed. Considering power allocation, a mixed-integer programing model for the optimisation of JRA is further established. A two-track simultaneous update binary particle swarm algorithm (TS-BPSO) is then devised to obtain the solutions of the JRA. Finally, the effectiveness of the proposed method for multiple jammers in the multiple missiles scenario is evaluated through simulations. The simulation results suggest that the distributed cooperative jamming resource allocation is affected by the incoming orientation of the missile and the relative position of the jammers and the targets. The findings of the study enable evaluating the use of jammer formations and provide insights into developing effective jamming strategies. K E Y W O R D S distributed outboard jammers, jamming effectiveness assessment, jamming resources allocation, multi-missile threat, TS-BPSO This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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.…”

A Study of Jamming Resource Allocation Based on a Hyperheuristic Framework

“…The radar network system, which is widely used instead of single radar, connects the sensors in the battle eld to each other, making the topology structure more complex 7 . The corresponding combat model exhibits multilevel and distributed characteristics 8, 9 . The concept and technology of cognitive radar are developing rapidly.…”

Cooperative jamming resource allocation model and algorithm for netted radar

“…Evaluation of jamming effect is the basis of resource allocation model, [1][2][3][4] used the form of membership function to evaluate the jamming effectiveness. Detection probability and aiming probability which reflect the detection and tracking capability of netted radar are used respectively in [5][6][7] as evaluation functions of jamming effect, the two are both considered in [8] to establish a jamming resource allocation model.…”

“…Many heuristic algorithms have been improved to solve the problem, such as the firefly algorithm [1], genetic algorithm [2], particle swarm algorithm [3,[5][6][7] and cuckoo algorithm [8].…”

“…where P fa represents the false alarm probability of the radar, I denotes the number of non-coherent accumulated pulses. The rank K judgement criterion is used to calculate the fusion detection probability of radar network [5][6][7][8], which indicates that when there are K or more than K radars in the net discovering target at the same time, the netted radar system determines that the target is found. The detailed calculation formula of the fusion detection probability can be referred to [8], the computation is simply expressed as Equation (7) in this letter.…”