A class of polynomial rooting algorithms for joint azimuth/elevation estimation using multidimensional arrays

Polynomial rooting techniques for efficient high resolution estimation of direction parameters from linear arrays are well documented in the literature. These techniques are limited, however, to cases of estimating a scalar direction parameter (say, either azimuth or elevation). The paper introduces a methodology for extending the polynomial rooting philosophy to the case of multidimensional arrays, which will be used to estimate jointly both azimuth and elevation parameters of the signal directions. It is shown via simulation that the resolution capabilities of the polynomial root intersection for multidimensional estimation (PRIME) class of algorithms is superior to the spectral algorithms they supplant, and that the variance of the direction estimates is equal to that of the corresponding spectral algorithms. It is shown analytically that the mean squared error of the PRIME estimates can be asymptotically equal to that of spectral MUSIC estimates. Finally, some extensions are discussed