Skip to main navigation Skip to search Skip to main content

Polarization HRRP Target Recognition Neural Network Based on Adaptive Feature Fusion

  • Yangbo Zhou*
  • , Xiaomin Pan
  • , Sen Liu
  • *Corresponding author for this work
  • Beijing Institute of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A novel dual-polarization HRRP feature fusion neural network is proposed to exploit complementary information from HH and VH polarizations. Experiments on a dataset of ten low-orbit satellites demonstrate that the proposed network outperforms single-polarization methods in fine-grained recognition, maintaining high accuracy across various SNR conditions, thus validating its robustness in complex electromagnetic environments.

Original languageEnglish
Title of host publicationISEMC 2025 - 8th International Symposium on Electromagnetic Compatibility, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798331579159
DOIs
Publication statusPublished - 2025
Externally publishedYes
Event8th IEEE International Symposium on Electromagnetic Compatibility, ISEMC 2025 - Hefei, China
Duration: 10 Oct 202512 Oct 2025

Publication series

NameISEMC 2025 - 8th International Symposium on Electromagnetic Compatibility, Proceedings

Conference

Conference8th IEEE International Symposium on Electromagnetic Compatibility, ISEMC 2025
Country/TerritoryChina
CityHefei
Period10/10/2512/10/25

Keywords

  • Deep Learning
  • Feature Fusion
  • Polarization Features
  • Radar Target Recognition

Fingerprint

Dive into the research topics of 'Polarization HRRP Target Recognition Neural Network Based on Adaptive Feature Fusion'. Together they form a unique fingerprint.

Cite this