Radar Active Composite Jamming Recognition Method Based on STFT Feature Extraction

作者：Zhuochen Chen, Shengqi Zhu, Ximin Li, Zhongyi Guan, Minghui Sha, Hui Fang · 年份：2024 · DOI：10.1109/icicsp62589.2024.10809312 · 被引用次数：4 · 研究领域：Optical Systems and Laser Technology、Advanced Measurement and Detection Methods、Advanced SAR Imaging Techniques

To accurately identify radar active jamming in complex electromagnetic environments, this article constructed a library of typical suppression and deception jamming models and performed time-domain and frequency-domain feature extraction on their mixed composite jamming signals, obtaining sixteen feature parameters. To enhance the recognition rate of composite jamming, we proposed a Short-Time Fourier transform (STFT) feature extraction method, which additionally extracted seven feature parameters. Finally, we designed a cascaded Back Propagation (BP) neural network algorithm, employing a two-layer neural network to identify the composite jamming. Simulation results demonstrate that the proposed algorithm effectively identifies six types of composite jamming signals, and the inclusion of STFT features significantly improves the jamming recognition rate compared to traditional methods.