Efficient direction and polarization estimation with a COLD array

This paper considers angle and polarization estimation by means of a cocentered orthogonal loop and dipole (COLD) array. We show that by using the COLD array, the performance of both angle and polarization estimation can be greatly improved, as compared to using a crossed dipole array. We present an asymptotically statistically efficient method of direction estimation (MODE) algorithm that can be used with the COLD array for both angle and polarization estimation of correlated (including coherent) or uncorrelated incident signals. Numerical examples are given to show the better estimation performance of the MODE algorithm than that of the multiple signal classification (MUSIC) and the noise subspace-fitting (NSF) algorithms.