Spatial spectrum estimation in a coherent signal environment using an array in motion

Abstract

Spatial spectrum estimation utilizing an array in motion is here investigated for dealing with coherent arrivals in a multiple signal environment. The effect of estimating the spatial correlations while the array is moving is studied in terms of the decorrelation it produces, the change it causes in the eigenvalues of the correlation matrix, and the improvements obtained in the measured spectrum. Cases of both fixed and varying angle of arrival are investigated, The former arises with distant sources and will, with a sufficiently long estimation interval, emulate uncorrelated sources and given correspondingly sharp spectra. The latter arises with nearby sources and will allow them to be distinguished but will be attended by spectral shift and broadening, and loss of resolution. It is shown that meaningful estimates of the arrival angles can nevertheless be made. Specific illustrations are worked out using a seven-element, sparse, nonuniformly spaced linear array utilizing the well-known superresolution spectral estimators-the maximum likelihood (ML) method, the method of linear prediction (LP), and the method of multiple signal classification (MUSIC).