A Dynamic UAVs Cooperative Suppressive Jamming Method with Joint Task Assignment and Bandwidth Allocation

TL;DR

The paper develops a dynamic $D$-$MIP$ framework for UAV cooperative suppressive jamming of frequency agile radar networks, introducing a $\overline{JSR}$-based QoS utility to quantify jamming effectiveness across bandwidths. It presents a two-step dynamic hybrid algorithm that uses Kriging surrogates to predict utilities, alongside memory and random-immigrant strategies to cope with dynamic environments and computational limits. The outer stage optimizes discrete task assignments with GA guidance, while the inner stage solves continuous bandwidth allocations via a Kriging-guided, FROFI-inspired method. Simulation results demonstrate improved jamming performance, reduced computational resources, and robust adaptation to bandwidth estimation errors and varying cost factors. The approach enables scalable, real-time coordination of UAV swarms for defeating frequency-hopping radar networks.

Abstract

The low detectability and low cost of unmanned aerial vehicles (UAVs) allow them to swarm near the radar network for effective jamming. The key to jamming is the reasonable task assignment and resource allocation of UAVs. However, the existing allocation model is somewhat ideal, weakly adaptive to the dynamic environment, and rarely considers frequency matching, which cannot suppress the frequency agile radar (FAR) network effectively. To solve these problems, a dynamic UAVs cooperative suppressive jamming method with joint task assignment and bandwidth allocation is proposed. To represent the matching relationship between UAVs and FARs, a system model of task assignment and bandwidth allocation is established, the problem is formulated as a dynamic mixed integer programming (D-MIP) problem. Then, a suppressive jamming evaluation indicator is proposed, and the utility function is designed based on the Quality of Service (QoS) framework to quantify the jamming effect of UAVs. To solve the combinational optimization problem, a two-step dynamic hybrid algorithm based on Kriging model is proposed, which can obtain the task assignment and bandwidth allocation schemes of UAVs by consuming fewer computational resources in dynamic environment. Simulation results show that the proposed method is effective in terms of jamming performance, computational resource saving and dynamic environment adaptability.

Figures (12)

• Figure 1: Scene diagram of 6 UAVs suppressing 3 FARs to cover high-value target penetration where the legend indicates the bandwidth allocation of UAVs.
• Figure 2: UAV $n$ suppresses FAR $m$ under different bandwidth allocation at the $k$th frame. (a) UAV $n$ allocates a wide bandwidth; (b) UAV $n$ allocates a narrow bandwidth.
• Figure 3: Curves of suppressive jamming effect function $f({\rm \overline{JSR}}_{n,m,k})$ under different $L$.
• Figure 4: An example of 4 UAVs allocating certain bandwidth to jointly suppress the FAR $m$ at the $k$th frame.
• Figure 5: Flow chart of two-step dynamic hybrid algorithm based on Kriging model at the $k$th frame (TA: task assignment schemes, BA: bandwidth allocation schemes).

Theorems & Definitions (2)

• Remark 1
• Remark 2