Estimation of Near-Field Parameters using Spatial Time-Frequency Distributions

This work deals with the estimation of near-field parameters using passive sensor arrays. A transformation of the array data is proposed which allows the extraction of near-field time-frequency signatures from data containing a mixture of far- and near-field sources. Spatial time-frequency distribution matrices are then used as a means for solving the near-field parameter estimation problem. The estimation accuracy of the proposed approach is compared to existing methods via simulation analysis. An experimental validation of theoretical ideas is also presented.

[1]  Yimin Zhang,et al.  Subspace analysis of spatial time-frequency distribution matrices , 2001, IEEE Trans. Signal Process..

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

[4]  Moeness G. Amin,et al.  Blind source separation based on time-frequency signal representations , 1998, IEEE Trans. Signal Process..

[5]  Khaled H. Hamed,et al.  Time-frequency analysis , 2003 .

[6]  Abdelhak M. Zoubir,et al.  Estimation of Fm Parameters Using a Time-Frequency Hough Transform , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

[7]  Moeness G. Amin,et al.  Characterization of near-field scattering using quadratic sensor-angle distributions , 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.