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Space-Time Characteristic Analysis and Suppression Method Research of Directional Noise in HFSWR

  • School of Electronics and Information Engineering, Harbin Institute of Technology

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

Abstract

The ambient noise at any two different sensors, in practice, may correlate with each other, and the spatial distribution of ambient noise intensity may be directional because of extreme weather (thunderstorms, typhoons) or human factors (offshore wind farms, surrounding urban areas). Directional noise generally covers all doppler shift units and several angle units, and the noise level in doppler domain usually increases by 10-15 dB. Consequently, weak targets masked by directional noise are difficult to be detected. In this paper, Space-time adaptive processing (STAP) method is used to analyze the directional noise of High Frequency Surface Wave Radar (HFSWR). For the given measurements data set, we first researched the noise assess method, and then analyzed the range correlation, spatial correlation and space-time characteristics of directional noise. The results proved that directional noise has weak space-time coupling. Then, aiming at the problem of Local Processed Region (LPR) selection in joint domain localized (JDL) algorithm, this paper proposed an LPR selection method based on the multidimensional characteristics of directional noise. Finally, the experimental results have demonstrated that the improved LPR selection method is effective and the performance of weak target detection in directional noise is improved.

Original languageEnglish
Title of host publicationSPML 2022 - Proceedings of 2022 5th International Conference on Signal Processing and Machine Learning
PublisherAssociation for Computing Machinery
Pages118-123
Number of pages6
ISBN (Electronic)9781450396912
DOIs
StatePublished - 4 Aug 2022
Externally publishedYes
Event5th International Conference on Signal Processing and Machine Learning, SPML 2022 - Dalian, China
Duration: 4 Aug 20226 Aug 2022

Publication series

NameACM International Conference Proceeding Series

Conference

Conference5th International Conference on Signal Processing and Machine Learning, SPML 2022
Country/TerritoryChina
CityDalian
Period4/08/226/08/22

Keywords

  • Directional noise
  • HFSWR
  • LPR

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