Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/106676
Title: A decoupled approach for near-field source localization using a single acoustic vector sensor
Authors: Hari, V. N.
Premkumar, A. B.
Zhong, X.
Keywords: DRNTU::Engineering::Computer science and engineering
Issue Date: 2012
Source: Hari, V. N., Premkumar, A. B., & Zhong, X. (2013). A Decoupled Approach for Near-Field Source Localization Using a Single Acoustic Vector Sensor. Circuits, Systems, and Signal Processing, 32(2), 843-859.
Series/Report no.: Circuits, systems, and signal processing
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.
URI: https://hdl.handle.net/10356/106676
http://hdl.handle.net/10220/16641
DOI: 10.1007/s00034-012-9508-9
Schools: School of Computer Engineering 
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SCSE Journal Articles

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