Wenxu Zhang , Yajie Wang , Xiuming Zhou , Zhongkai Zhao , Feiran Liu
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引用次数: 0
Abstract
Aiming at the problem of interference resource scheduling in cognitive electronic warfare, a multi-objective interference power allocation method based on the proximal policy optimization (PPO) framework is proposed in this paper. Firstly, the confrontation between jammers and multi-objective radar networks is mapped as the interaction between the agent and the environment, and the radar target detection model under suppression interference is established. On this basis, an interference power allocation model against multi-objective radars based on PPO framework is constructed. Moreover, a reward normalization mechanism is introduced to optimize the reward setting, and an interference power allocation method based on optimized PPO is proposed. Meanwhile, this paper constructs a confrontation scenario in which the jammer covers the target aircraft to break through the multi-objective radar network. Simulation experiments are conducted based on this scenario to verify the effectiveness of the method proposed in this paper. The interference power allocation method proposed in this paper can intelligently adjust the power allocation scheme of the jammer according to the electromagnetic situation on the battlefield, optimize the resource utilization of the jammer, and occupy the initiative on the battlefield.
期刊介绍:
Signal Processing incorporates all aspects of the theory and practice of signal processing. It features original research work, tutorial and review articles, and accounts of practical developments. It is intended for a rapid dissemination of knowledge and experience to engineers and scientists working in the research, development or practical application of signal processing.
Subject areas covered by the journal include: Signal Theory; Stochastic Processes; Detection and Estimation; Spectral Analysis; Filtering; Signal Processing Systems; Software Developments; Image Processing; Pattern Recognition; Optical Signal Processing; Digital Signal Processing; Multi-dimensional Signal Processing; Communication Signal Processing; Biomedical Signal Processing; Geophysical and Astrophysical Signal Processing; Earth Resources Signal Processing; Acoustic and Vibration Signal Processing; Data Processing; Remote Sensing; Signal Processing Technology; Radar Signal Processing; Sonar Signal Processing; Industrial Applications; New Applications.