Robust direction-of-arrival estimation in non-Gaussian noise

A nonlinearly weighted least-squares method is developed for robust modeling of sensor array data, weighting functions for various observation noise scenarios are determined using maximum likelihood estimation theory. The computational complexity of the new method is comparable with the standard least-squares estimation procedures. Simulation examples of direction-of-arrival estimation are presented.