Maximum-likelihood spatial spectrum estimation in dynamic environments with a short maneuverable array.

Published

Journal Article

This work concerns the development of field directionality mapping algorithms for short acoustic arrays on mobile maneuverable platforms that avoid the left/right ambiguities and endfire resolution degradation common to longer non-maneuverable line arrays. In this paper, it is shown that short maneuverable arrays can achieve a high fraction of usable bearing space for target detection in interference-dominated scenarios, despite their lower array gain against diffuse background noise. Two narrowband techniques are presented which use the expectation-maximization maximum likelihood algorithm under different models of the time-varying field directionality. The first, derivative based maximum likelihood, uses a deterministic model while the second, recursive Bayes maximum likelihood, uses a stochastic model for the time-varying spatial spectrum. In addition, a broadband extension is introduced that incorporates temporal spectral knowledge to suppress ambiguities when the average sensor array spacing is greater than a half-wavelength. Dynamic multi-source simulations demonstrate the ability of a short, maneuvering array to reduce array ambiguities and spatial grating lobes in an interference dominated environment. Monte Carlo evaluation of receiver operating characteristics is used to evaluate the improvement in source detection achieved by the proposed methods versus conventional broadband beamforming.

Full Text

Duke Authors

Cited Authors

  • Odom, JL; Krolik, JL; Rogers, JS

Published Date

  • January 2013

Published In

Volume / Issue

  • 133 / 1

Start / End Page

  • 311 - 322

PubMed ID

  • 23297904

Pubmed Central ID

  • 23297904

Electronic International Standard Serial Number (EISSN)

  • 1520-8524

International Standard Serial Number (ISSN)

  • 0001-4966

Digital Object Identifier (DOI)

  • 10.1121/1.4770233

Language

  • eng