Parallel adaptive array processing for coherent sources

Abstract

The main objective of this dissertation is to develop an adaptive beamformer which is highly fast and numerically stable, and is capable of nulling out coherent interferences. Signal reception using an array of sensor elements is currently the subject of considerable interest because an array antenna system affords the means of break-throughs overcoming the directivity and resolution limitations of a single sensor element. The beam pattern of the adaptive array is automatically adjusted to create nulls in the directions of interfering signals, while passing a desired, look-direction signal with minimum distortion. Conventional beamformers so far studied require the assumption that interfering signals are not correlated with the desired signal. When this underlying assumption is no longer valid, the adaptive beamformer not only generates false nulls, but also tends to cancel the look-direction signal completely, resulting in a poor performance. In order to cope with the performance degradations due to the coherence between the desired signal and interferences, the spatial smoothing technique has been used. Although the method is found to be effective in combatting coherent interferences, it is disadvantageous in that the method significantly reduce the effective array aperture. To use the array aperture efficiently, the modified spatial smoothing technique has been developed. But, the method still forms covariance matrices as is the case of the original spatial smoothing technique, which difficulties when the wordlength is finite. Accordingly, to prevent the numerical instability caused by the spatial smoothing technique and its variations, one must have twice as long wordlength as the original data set particularly when the given data is ill-conditioned. In this dissertation, we present a data-domain modified spatial smoothing (DMSS) technique, by which the inter-signal correlation can be removed, and the formation of covariance matrices can be avoided. Since t...