Transform-based covariance differencing approach to the array with spatially nonstationary noise

The problem of bearing estimation in a situation where the additive white noise is assumed to be spatially nonstationary, i.e uncorrelated and of unequal power from sensor to sensor, is discussed. In this condition, the resolution of the standard methods decreases and the problem of source enumeration becomes more involved. A transform-based covariance differencing approach is proposed to resolve the problems of enumerating sources and estimating their bearings. Performance of the proposed method is compared with that of MUSIC via simulation