Recursive least-squares source tracking using one acoustic vector sensor

Mohamad Khattar Awad, Kainam Thomas Wong

Research output: Journal article publicationJournal articleAcademic researchpeer-review

38 Citations (Scopus)

Abstract

An acoustic vector-sensor (a.k.a. vector-hydrophone) is composed of three acoustic velocity-sensors, plus a collocated pressure-sensor, all collocated in space. The velocity-sensors are identical, but orthogonally oriented, each measuring a different Cartesian component of the three-dimensional particle-velocity field. This acoustic vector-sensor offers an azimuth-elevation response that is invariant with respect to the source's center frequency or bandwidth. This acoustic vector-sensor is adopted here for recursive least-squares (RLS) adaptation, to track a single mobile source, in the absence of any multipath fading and any directional interference. A formula is derived to preset the RLS forgetting factor, based on the prior knowledge of only the incident signal power, the incident source's spatial random walk variance, and the additive noise power. The work presented here further advances a multiple-forgetting-factor (MFF) version of the RLS adaptive tracking algorithm, that requires no prior knowledge of these aforementioned source statistics or noise statistics. Monte Carlo simulations demonstrate the tracking performance and computational load of the proposed algorithms.
Original languageEnglish
Article number6324678
Pages (from-to)3073-3083
Number of pages11
JournalIEEE Transactions on Aerospace and Electronic Systems
Volume48
Issue number4
DOIs
Publication statusPublished - 22 Oct 2012

ASJC Scopus subject areas

  • Aerospace Engineering
  • Electrical and Electronic Engineering

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