Multi-Channel Lightweight Contrast Prediction Coding for Features Extraction of Radar Emitter Signals

Junning Zhang, Zhanyang Wei, Guoru Ding, Junli Liang, Zefeng Zhang

Research output: Contribution to journalArticlepeer-review

Abstract

This letter presents a novel multi-channel improved contrastive predictive coding (CPC) method to extract signals features. Specifically, to extract low pulse width radar signals features and meet the real-time requirements of signals identification, we design a lightweight encoder to realize the CPC features encoding function. Then, we construct a multi-channel CPC features decoder to mine and extract subtle individual signals features from the perspective of multi-domain and multi-channel information input. Simulation results verify the effectiveness of our proposed method, which can achieve state-of-the-art results in both accuracy and running time compared to the existing optimal methods. All our models and code are available at https://github.com/jn-z/MC-CPC.

Original languageEnglish
Article number246
JournalNeural Processing Letters
Volume56
Issue number6
DOIs
StatePublished - Dec 2024

Keywords

  • Contrastive predictive coding (CPC)
  • Lightweight encoder
  • Multi-channel decoder
  • Signals features extraction

Fingerprint

Dive into the research topics of 'Multi-Channel Lightweight Contrast Prediction Coding for Features Extraction of Radar Emitter Signals'. Together they form a unique fingerprint.

Cite this