Maneuverable-Jamming-Aided Secure Communication and Sensing in A2G-ISAC Systems

TL;DR

This paper introduces a maneuverable jamming-assisted scheme for secure communication and sensing in A2G-ISAC systems, optimizing UAV trajectories and beamforming to maximize secrecy rate while considering interference and resource constraints.

Contribution

It proposes a two-phase joint optimization framework for UAV trajectory and beamforming in secure A2G-ISAC, addressing the trade-off between communication and sensing performance.

Findings

Achieves the highest average secrecy rate compared to benchmarks.

Demonstrates robustness of the scheme under residual interference.

Shows the impact of SIC residual interference on system performance.

Abstract

In this paper, we propose a maneuverablejamming-aided secure communication and sensing (SCS) scheme for an air-to-ground integrated sensing and communication (A2G-ISAC) system, where a dual-functional source UAV and a maneuverable jamming UAV operate collaboratively in a hybrid monostatic-bistatic radar configuration. The maneuverable jamming UAV emits artificial noise to assist the source UAV in detecting multiple ground targets while interfering with an eavesdropper. The effects of residual interference caused by imperfect successive interference cancellation on the received signal-to-interference-plus-noise ratio are considered, which degrades the system performance. To maximize the average secrecy rate (ASR) under transmit power budget, UAV maneuvering constraints, and sensing requirements, the dual-UAV trajectory and beamforming are jointly optimized. Given that secure communication and sensing fundamentally conflict in terms of resource allocation, making it difficult to achieve optimal performance for both simultaneously, we adopt a two-phase design to address this challenge. By dividing the mission into the secure communication (SC) phase and the SCS phase, the A2G-ISAC system can focus on optimizing distinct objectives separately. In the SC phase, a block coordinate descent algorithm employing the trust-region successive convex approximation and semidefinite relaxation iteratively optimizes dual-UAV trajectory and beamforming. For the SCS phase, a weighted distance minimization problem determines the suitable dual-UAV sensing positions by a greedy algorithm, followed by the joint optimization of source beamforming and jamming beamforming. Simulation results demonstrate that the proposed scheme achieves the highest ASR among benchmarks while maintaining robust sensing performance, and confirm the impact of the SIC residual interference on both secure communication and sensing.