Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/96053
Title: Particle filtering and posterior Cramér-Rao bound for 2-D direction of arrival tracking using an acoustic vector sensor
Authors: Premkumar, A. B.
Madhukumar, A. S.
Zhong, Xionghu
Keywords: DRNTU::Engineering::Computer science and engineering
Issue Date: 2011
Source: Zhong, X., Premkumar, A. B., Madhukumar, A. S. (2011). Particle filtering and posterior Cramér-Rao bound for 2-D direction of arrival tracking using an acoustic vector sensor. IEEE Sensors Journal, 12(2), 363-377.
Series/Report no.: IEEE sensors journal
Abstract: Acoustic vector sensor (AVS) measures acoustic pressure as well as particle velocity, and therefore AVS signal contains 2-D (azimuth and elevation) DOA information of an acoustic source. Existing DOA estimation techniques assume that the source is static and extensively rely on the localization methods. In this paper, a particle filtering (PF) tracking approach is developed to estimate the 2-D DOA from signals collected by an AVS. A constant velocity model is employed to model the source dynamics and the likelihood function is derived based on a maximum likelihood estimation of the source amplitude and the noise variance. The posterior Cramér-Rao bound (PCRB) is also derived to provide a lower performance bound for AVS signal based tracking problem. Since PCRB incorporates the information from the source dynamics and measurement models, it is usually lower than traditional Cramér-Rao bound which only employs measurement model information. Experiments show that the proposed PF tracking algorithm significantly outperforms Capon beamforming based localization method and is much closer to the PCRB even in a challenging environment (e.g., SNR = -10 dB).
URI: https://hdl.handle.net/10356/96053
http://hdl.handle.net/10220/11225
DOI: http://dx.doi.org/10.1109/JSEN.2011.2168204
Rights: © 2011 IEEE.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SCSE Journal Articles

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