A Spectral Clustering Sorting Method For Radar Signals Based On SOM Anchor Extraction And Graph Fusion

  • Ziying Li
  • , Min Xie
  • , Jian Dong
  • , Ying Ma
  • , Jun Yang
  • , Xiongjun Fu*
  • *Corresponding author for this work

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

1 Citation (Scopus)

Abstract

As a key technology of reconnaissance system, radar signal sorting (RSS) aims to separate the pulse sequence emitted by different radar from received pulse stream. However, with the emergence of multi-function radars (MFRs), the complex distribution of pulses presents challenges for radar signal sorting in the battlefield electromagnetic environments. A spectral clustering sorting method for radar signal (WFG-SC) is proposed to tackle the problem mentioned above. Our method utilizes Self-Organizing Map (SOM) and K-nearest neighbors (KNN) to construct an adaptive topological graph of the pulse stream. Then, the spectral clustering algorithm is employed for radar signal sorting. Simulation results on MFR pulse dataset show that our method improves the performance of spectral clustering and outperforms some existing sorting methods.

Original languageEnglish
Title of host publicationIEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798331515669
DOIs
Publication statusPublished - 2024
Event2nd IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024 - Zhuhai, China
Duration: 22 Nov 202424 Nov 2024

Publication series

NameIEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024

Conference

Conference2nd IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024
Country/TerritoryChina
CityZhuhai
Period22/11/2424/11/24

Keywords

  • Radar signal sorting
  • anchor graph
  • self-organizing map
  • spectral clustering

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