Conference_programme: 21: Source identification and localization

Lecture: DIRECTION OF ARRIVAL ESTIMATION ALGORITHM FOR RECTANGULAR ARRAYS USING FULL EIGEN SPACE

Author(s): Singh Arun Prakash

Summary:
It is well known that, sound field is often measured by microphone array. For localization of sound source, the Direction of Arrival (DOA) of signal is estimated. A typical sound has two angular co-ordinates (DOA); the azimuth angle and the elevation angle. Linear microphone arrays provide information only on the azimuth angle of the sound source. For estimation of a pair of parameters we need minimum two dimensional array. Square or rectangular array is extension of linear array, where the sensors are placed on a square or rectangular grid, and used for estimation of both angular co-ordinates. Also there are several methods for estimation of direction of arrival of sound (DOA) through measured data. In these methods, delay of time difference of arrival of sound between reference microphones to each microphone is calculated and used for DOA estimation. Most classic method for DOA estimation algorithm is MUSIC, based on Eigen decomposition of covariance matrix of measured data. Eigen decomposition gives eigenvalue and eigenvectors of signal and noise subspaces but only noise subspace eigenvector is used to search the peak of MUSIC spectrum to get DOA information of sound signal. It is observed that, estimation of DOA of multiple sound signal give better results when DOA estimation algorithm makes full use of signal subspace and noise subspace characteristics. In this paper a novel DOA estimation algorithm is proposed for rectangular array using full Eigen space. The simulation results shows that the performance of proposed algorithm gives better estimation of DOA in the conditions of small snapshot as well as low SNR.\nKeywords: Music, DOA, Microphone Array Signal Processing, Signal Subspace, Noise Subspace\n

Corresponding author

Name: Mr Arun Prakash Singh

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Country: India