Array processing deals with methods for processing the output data of an array of sensors located at different positions in space in a wavefield. The purpose of the array processing is to obtain insight into the structure of the waves carrying information and traversing the array. Array processing methods have been extensively studied, and results can be found in the literature on radio astronomy, electrical engineering, acoustics, geophysics and statistics.
Recently a group of methods known as the high resolution array processing methods have been developed. All these methods make the assumption that the signals arriving at the array are generated by point sources in space. However, in many practical situations, this assumption is invalid leading to the break down of the high resolution methods.
This thesis is devoted to the study on high resolution array processing methods of the location parameters of physically dispersed sources that generate the signals. The formulation and the properties of spatially dispersed sources are presented. The geometric structure of the data space is examined which enables the partitioning of signal and noise subspaces from which several methods for source localization are proposed. The performance of these methods are analyzed. Engineering applications of this research topic are discussed.