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Direction-finding of coherent sources via ‘particle-velocity-field smoothing’

Direction-finding of coherent sources via ‘particle-velocity-field smoothing’

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  • Author(s): J. Tao 1 ; W. Chang 2 ; Y. Shi 2
    • View affiliations
    • Affiliations: 1: Department of Control Engineering, Aviation University, Changchun, People's Republic of China
      2: College of Communication Engineering, Jilin University, Changchun, People's Republic of China
  • Source: Volume 2, Issue 2, April 2008, p. 127 – 134
    DOI:  10.1049/iet-rsn:20050140 , Print ISSN 1751-8784, Online ISSN 1751-8792
© The Institution of Engineering and Technology
Published

A new ‘particle-velocity-field smoothing’ (PVFS) algorithm is proposed to decorrelate up to three coherent sources for azimuth-elevation direction-finding using vector-hydrophones in the underwater acoustic medium. The coherency among the incident sources would reduce the data correlation matrix's rank to below the number of incident sources, but this proposed algorithm restores the rank by summing the individual particle-velocity-field component's data correlation matrices. This scheme uses identically oriented underwater-acoustic vector-hydrophones, its locations may be arbitrary. Each underwater-acoustic vector-hydrophone consists of two or three collocated but orthogonally oriented velocity-hydrophones, and a pressure-hydrophone. In contrast to the customary ‘spatial smoothing’ technique, this proposed PVFS algorithm does not reduce the array's spatial aperture and does not require any ‘virtual array interpolation’ even for an irregularly shaped array grid. Monte Carlo simulations verify this proposed scheme's efficacy.

Inspec keywords: signal classification; hydrophones; Monte Carlo methods; underwater sound

Other keywords: underwater acoustic medium; data correlation matrix; data correlation matrices; Monte Carlo simulations; vector-hydrophones; azimuth-elevation direction-finding; shaped array grid; particle-velocity-field smoothing; coherent sources

Subjects: Signal processing and detection; Monte Carlo methods; Underwater sound; Probability theory, stochastic processes, and statistics

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