A Decoupled Approach for Near-Field Source Localization Using a Single Acoustic Vector Sensor
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A Decoupled Approach for Near-Field Source Localization Using a Single Acoustic Vector Sensor V.N. Hari · A.B. Premkumar · X. Zhong
Received: 28 March 2012 / Revised: 2 October 2012 / Published online: 24 October 2012 © Springer Science+Business Media New York 2012
Abstract This paper considers the problem of three-dimensional (3-D, azimuth, elevation, and range) localization of a single source in the near-field using a single acoustic vector sensor (AVS). The existing multiple signal classification (MUSIC) or maximum likelihood estimation (MLE) methods, which require a 3-D search over the location parameter space, are computationally very expensive. A computationally simple method previously developed by Wu and Wong (IEEE Trans. Aerosp. Electron. Syst. 48(1):159–169, 2012), which we refer to as Eigen-value decomposition and Received Signal strength Indicator-based method (Eigen-RSSI), was able to estimate 3-D location parameters of a single source efficiently. However, it can only be applied to an extended AVS which consists of a pressure sensor separated from the velocity sensors by a certain distance. In this paper, we propose a uni-AVS MUSIC (U-MUSIC) approach for 3-D location parameter estimation based on a compact AVS structure. We decouple the 3-D localization problem into step-by-step estimation of azimuth, elevation, and range and derive closed-form solutions for these parameter estimates by which a complex 3-D search for the parameters can be avoided. We show that the proposed approach outperforms the existing Eigen-RSSI method when the sensor system is required to be mounted in a confined space. Keywords Acoustic vector sensor · Localization · Near-field · MUSIC · DOA estimation V.N. Hari () · A.B. Premkumar · X. Zhong School of Computer Engineering, Nanyang Technological University, CeMNet Annexe, Block N4, B2b-05, Singapore 639798, Singapore e-mail: [email protected] A.B. Premkumar e-mail: [email protected] X. Zhong e-mail: [email protected]
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Circuits Syst Signal Process (2013) 32:843–859
1 Introduction An acoustic vector sensor (AVS) is capable of measuring particle velocities and acoustic pressure at a point in space and can estimate the direction of arrival (DOA) of a source unambiguously [8, 17, 33]. Both theoretical studies and experimental setups such as the DIFAR (DIrectional Frequency Analysis and Recording) array [3] and the recently conducted Makai experiment [18] have shown that an AVS is superior to the traditional acoustic pressure sensor in DOA estimation. In the recent past, array signal processing approaches such as the Capon beamformer [8], multiple signal classification (MUSIC) [31, 39], estimation of signal parameters via rotational invariance (ESPRIT) [25, 27–29], Root-MUSIC [30], and other approaches [2, 10, 11, 16, 35] have been employed for AVS-signal-based DOA estimation. The impressive performance of the vector sensors has also been demonstrated in numerous other signal processing problems such as source tracking [5, 36–38], detection [6, 7, 38], communication
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