Narrowband array processing algorithms for arbitrary noise distributions

Array processing algorithms generally assume that the received signal, composed of both narrowband signals and noise, is Gaussian. This is not true in general. In the context of the narrowband array processing problem, the authors develop robust methods to estimate accurately the spatial correlation matrix. This estimate is robust against amplitude distribution of the noise, be it Gaussian or not, and takes into account sensor placement. Given this estimate, existing array processing algorithms designed for Gaussian circumstances can be used on non-Gaussian problems. The resulting algorithms can be used in the presence of any type of second-order noise process and perform nearly as well as existing algorithms do with Gaussian noise