A weighted linear prediction method for near-field source localization

This paper proposes a low computational cost method for the near-field narrowband source localization problem, which does not require multidimensional search or high-order statistics. The proposed method is based on the second-order statistics (SOS) of the outputs of a uniform linear array (ULA). More precisely, the range and angle parameters are estimated through a weighted linear prediction (LP) algorithm applied to a properly chosen array output correlation sequence. Detailed performance analysis and derivation of the optimal weightings are provided. Simulation results are finally presented to validate the theoretical analysis results and to assess the performance of the proposed method.

[1]  Michael D. Zoltowski,et al.  Near-field/far-field azimuth and elevation angle estimation using a single vector hydrophone , 2001, IEEE Trans. Signal Process..

[2]  M. Viberg,et al.  Two decades of array signal processing research: the parametric approach , 1996, IEEE Signal Process. Mag..

[3]  Kung Yao,et al.  Maximum-likelihood source localization and unknown sensor location estimation for wideband signals in the near-field , 2002, IEEE Trans. Signal Process..

[4]  M. Barkat,et al.  Near-field multiple source localization by passive sensor array , 1991 .

[5]  Hsien-Sen Hung,et al.  3-D MUSIC with polynomial rooting for near-field source localization , 1996, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings.

[6]  Ralph Otto Schmidt,et al.  A signal subspace approach to multiple emitter location and spectral estimation , 1981 .

[7]  Jean-Jacques Fuchs,et al.  On the application of the global matched filter to DOA estimation with uniform circular arrays , 2000, 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100).

[8]  Hideki Asoh,et al.  Sound source localization and signal separation for office robot "JiJo-2" , 1999, Proceedings. 1999 IEEE/SICE/RSJ. International Conference on Multisensor Fusion and Integration for Intelligent Systems. MFI'99 (Cat. No.99TH8480).

[9]  Thomas Kailath,et al.  ESPRIT-estimation of signal parameters via rotational invariance techniques , 1989, IEEE Trans. Acoust. Speech Signal Process..

[10]  H.A. Cirpan,et al.  Unconditional maximum likelihood approach for near-field source localization , 2001, ICECS 2001. 8th IEEE International Conference on Electronics, Circuits and Systems (Cat. No.01EX483).

[11]  S. Shamsunder,et al.  High-order subspace-based algorithms for passive localization of near-field sources , 1995, Conference Record of The Twenty-Ninth Asilomar Conference on Signals, Systems and Computers.

[12]  Jean-Jacques Fuchs,et al.  Near-field sources localization: a model-fitting approach , 1995, 1995 International Conference on Acoustics, Speech, and Signal Processing.

[13]  Hakan A. Çirpan,et al.  Maximum likelihood 3-D near-field source localization using the EM algorithm , 2003, Proceedings of the Eighth IEEE Symposium on Computers and Communications. ISCC 2003.

[14]  Björn E. Ottersten,et al.  Detection and estimation in sensor arrays using weighted subspace fitting , 1991, IEEE Trans. Signal Process..

[15]  Benjamin Friedlander,et al.  Performance analysis of higher order ESPRIT for localization of near-field sources , 1998, IEEE Trans. Signal Process..

[16]  Ju-Hong Lee,et al.  Estimating the bearings of near-field cyclostationary signals , 2002, IEEE Trans. Signal Process..

[17]  Y. Hua,et al.  A weighted linear prediction method for near-field source localization , 2002, IEEE Transactions on Signal Processing.

[18]  Anthony J. Weiss,et al.  Range and bearing estimation using polynomial rooting , 1993 .

[19]  A. Belouchrani,et al.  Second-order near-field source localization: algorithm and performance analysis , 1996, Conference Record of The Thirtieth Asilomar Conference on Signals, Systems and Computers.

[20]  Philippe Loubaton,et al.  Second order blind equalization in multiple input multiple output FIR systems: a weighted least squares approach , 1996, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings.

[21]  N. L. Owsley,et al.  Array phonocardiography , 2000, Proceedings of the IEEE 2000 Adaptive Systems for Signal Processing, Communications, and Control Symposium (Cat. No.00EX373).

[22]  Tapan K. Sarkar,et al.  Matrix pencil method for estimating parameters of exponentially damped/undamped sinusoids in noise , 1990, IEEE Trans. Acoust. Speech Signal Process..

[23]  Yoram Bresler,et al.  Exact maximum likelihood parameter estimation of superimposed exponential signals in noise , 1986, IEEE Trans. Acoust. Speech Signal Process..

[24]  T. Kailath,et al.  Passive direction-of-arrival and range estimation for near-field sources , 1988, Fourth Annual ASSP Workshop on Spectrum Estimation and Modeling.

[25]  P. Stoica,et al.  The stochastic CRB for array processing: a textbook derivation , 2001, IEEE Signal Processing Letters.

[26]  S. Shamsunder,et al.  Improved bearing and range estimation via high-order subspace based Unitary ESPRIT , 1996, Conference Record of The Thirtieth Asilomar Conference on Signals, Systems and Computers.

[27]  W. M. Carey,et al.  Digital spectral analysis: with applications , 1986 .

[28]  Eric Moulines,et al.  Asymptotic performance analysis of direction-finding algorithms based on fourth-order cumulants , 1995, IEEE Trans. Signal Process..

[29]  Fatma Ayhan Sakarya,et al.  A unified neural-network-based speaker localization technique , 2000, IEEE Trans. Neural Networks Learn. Syst..

[30]  Ju-Hong Lee,et al.  A covariance approximation method for near-field direction-finding using a uniform linear array , 1995, IEEE Trans. Signal Process..