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Multidimensional Systems and Signal Processing

, Volume 26, Issue 1, pp 321–336 | Cite as

DOA estimation of moving sound sources in the context of nonuniform spatial noise using acoustic vector sensor

  • Yong Jin
  • Xianxing Liu
  • Zhentao Hu
  • Song Li
  • Yunshan Hou
Article

Abstract

In this paper, DOA estimation of moving sound source using an acoustic vector-sensor in the context of spatially nonuniform noise is discussed. We propose a novel method for DOA tracking. In this method, non-uniform noise covariance is first estimated using acoustic vector sensor measurement and then the weighted parameter of conventional maximum power (MP) method is fixed by noise pre-whitening technique. In this way the weighted parameter selection problem of MP is solved when the noise powers of monopole and dipole are unknown. Moreover, under the assumption of constant velocity model of source dynamics, the DOA estimation by the improved maximum energy method is treated as measuring information and the Kalman filter algorithm in polar coordinate system is introduced to improve the accuracy of DOA estimation of moving sources. Theoretical analysis and simulation results demonstrate that the mean square angle error of the proposed method is lower than the traditional Cramer–Rao lower bound which only employs static measurement information.

Keywords

DOA Acoustic vector sensor Moving sound source  Kalman filter 

Notes

Acknowledgments

This work is supported by the National Nature Science Foundation of China (No. U1204611, No. 61300214 and No. 61374134), Nature Science Foundation of Henan Province of China (132300410278, 132300410148) and Science and Technology Innovation Team Support Program of Henan Province, China (13IRTSTHN021).

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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Yong Jin
    • 1
  • Xianxing Liu
    • 1
  • Zhentao Hu
    • 1
  • Song Li
    • 1
  • Yunshan Hou
    • 1
  1. 1.Institute of Image Processing and Pattern RecognitionHenan UniversityKaifeng China

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