Locating wide band acoustic sources using higher order statistics

The conventional array processing algorithms are effective when the propagation model and the array geometry are known and when the additive noise is white or with a known covariance matrix. In several real situations these assumptions are not verified, hence a degradation of their performances. To cope with this problem, we resort to the higher order statistics of the received signals. The interest of the published papers was the separation of the narrow band and uncorrelated acoustic sources. In this paper, we propose a cumulant based algorithm to characterize the wide band and fully correlated signals. This algorithm removes the additive Gaussian noise and then improves the existing narrow band array processing techniques. This method consists in combining the different information contained in the analysis band by using the optimal transformation matrices. The basic idea is based on both the fourth order statistics and the whitening processing of the received data. This leads to cleaned data and then to improve the source separation. The performance of the proposed algorithm is obtained by simulations for several test cases of interest.