A neural structure for direction finding with sensor array uncertainties

Authors:
Jiankan Yang;Qiang Wu;James P. Reilly
Affiliations:
Dept. of Electrical Engineering, Brigham Young University, Provo, Utah;Communication Research Laboratory, McMaster University, Hamilton, Ontario;Communication Research Laboratory, McMaster University, Hamilton, Ontario
Venue:
ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: plenary, special, audio, underwater acoustics, VLSI, neural networks - Volume I
Year:
1993

Citing 1
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Experimental performance of calibration and direction-finding algorithms

ICASSP '91 Proceedings of the Acoustics, Speech, and Signal Processing, 1991. ICASSP-91., 1991 International Conference

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Abstract

This paper presents an auto-calibration technique to estimate the DOAs of unknown signals in the presence of sensor gain and phase errors. Compared with other auto-calibration algorithms, this algorithm is computationally more efficient, and has a unique solution for a linear array with the imposed constraints. Furthermore, the complex computation in the objective likelihood gradients is performed by neural networks. An analogue scheme encompassing neural networks has been proposed for the algorithm's implementation.