Underdetermined DOA estimation of wideband non-stationary signals with completely overlapped TFDs

Jiahui Bing, Yougen Xu*, Yi Liang

*Corresponding author for this work

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

Abstract

An underdetermined direction-of-arrival (DOA) estimation method is proposed for wideband non-stationary signals with completely overlapped time-frequency distributions (TFDs). In this case, signals cannot be separated based solely on their time-frequency characteristics because of a rank-deficient spatial time-frequency distribution (STFD) matrix. The proposed method uses a moving array to recover the rank of the STFD matrix. Meantime, it vectorizes the matrix to construct a differential virtual co-array, and employs matrix rank minimization to fill the holes of virtual array, thereby enhancing the array processing degree of freedom. This method enables underdetermined DOA estimation of wideband non-stationary signals with completely overlapped TFDs, without suffering from aperture loss or requiring arrays with spatial translation invariant structures. Simulation results demonstrate the effectiveness of the proposed method.

Original languageEnglish
Title of host publicationFifth International Conference on Signal Processing and Computer Science, SPCS 2024
EditorsHaiquan Zhao, Lei Chen
PublisherSPIE
ISBN (Electronic)9781510686724
DOIs
Publication statusPublished - 2025
Event5th International Conference on Signal Processing and Computer Science, SPCS 2024 - Harbin, China
Duration: 23 Aug 202425 Aug 2024

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume13442
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

Conference5th International Conference on Signal Processing and Computer Science, SPCS 2024
Country/TerritoryChina
CityHarbin
Period23/08/2425/08/24

Keywords

  • matrix rank minimization
  • moving sparse array
  • underdetermined DOA estimation
  • wideband non-stationary signals

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