SPARSE BAYESIAN SYNTHETIC APERTURE PROCESSING BASED DOA ESTIMATION WITH DEFORMED TOWED ARRAYS

Jie Yang, Yixin Yang, Bin Liao

Research output: Contribution to journalConference articlepeer-review

1 Scopus citations

Abstract

In this paper, we present a new synthetic aperture method for direction-of-arrival (DOA) estimation using a passive towed sonar array that is deformed during platform maneuver. With certain prior knowledge of source-array geometry, we propose to find the optimal maximum likelihood estimates of DOAs and sensor positions by maximizing the model evidence of these parameters and the array observations. In order to tackle the resulting complex problem, the variational Bayesian Expectation-Maximization framework is employed. The proposed method is capable of achieving improved angular resolution by aperture synthesis and is robust to perturbations in the array manifold. Numerical simulations illustrate statistical efficiency of the proposed technique.

Original languageEnglish
Pages (from-to)13161-13165
Number of pages5
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
DOIs
StatePublished - 2024
Event2024 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2024 - Seoul, Korea, Republic of
Duration: 14 Apr 202419 Apr 2024

Keywords

  • Direction-of-arrival (DOA) estimation
  • deformed towed array
  • variational Bayesian

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