针对现代战场雷达电子对抗中侦察精度不足、干扰自适应弱及验证平台成本高的问题，本文基于Python设计雷达系统的侦察-干扰全流程技术方案。核心设计包括：轻量化雷达信号识别模型，以MobileNetV3为基础，结合知识蒸馏与小波去噪，实现LFM/BPSK等信号的快速识别；智能干扰技术，通过PPO模型优化干扰策略（压制/欺骗切换），DCGAN生成高逼真假目标信号；构建4层Python仿真平台，集成数据生成、模型训练、交互可视化与硬件对接功能。仿真实验结果表明，相比DDPG、A3C等主流智能干扰算法，PPO模型的压制式干扰成功率、欺骗式干扰成功率及平均JSR、平均Pdecept以及干扰响应时间均显著更优。
Aiming at the problems of insufficient reconnaissance accuracy, weak interference adaptability and high cost of verification platform in modern battlefield radar electronic countermeasures, this paper designs a full-process technical solution for reconnaissance and interference of the radar system based on Python. The core design includes: A lightweight radar signal recognition model, based on MobileNetV3, combined with knowledge distillation and wavelet denoising, to achieve rapid recognition of LFM/BPSK and other signals; Intelligent interference technology, optimizing interference strategies (suppression/deception switching) through the PPO model, and generating highly realistic false target signals with DCGAN; Build a four-layer Python simulation platform, integrating data generation, model training, interactive visualization and hardware connection functions. The simulation experiment results show that, compared with mainstream intelligent interference algorithms such as DDPG and A3C, the success rate of suppressed interference, the success rate of deceptive interference, the average JSR, the average Pdecept, and the interference response time of the PPO model are all significantly better.
2025,47(20): 185-189 收稿日期：2025-9-22
DOI：10.3404/j.issn.1672-7649.2025.20.029
分类号：U667.65
基金项目：江西省教育厅科学技术研究项目（GJJ2207513）；江西省教育厅科学技术研究项目（GJJ2407706）
作者简介：胡荣(1986-),女,硕士,副教授,研究方向为电子与通信工程及人工智能
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