Comparative performance of different adaptive superresolution array algorithms

Superresolution techniques provide precise details of the observed signal environment. The performance of different adaptive superresolution array algorithms that utilize the Howell-Applebaum technique is compared. The algorithms considered in this work are Gabierl´s thermal noise, adaptive angular response, and maximum-likelihood method. Two different cases are discussed. Firstly, the antenna array is subjected to only one signal plus thermal noise. Secondly, the case of the presence of two incident signals plus thermal noise is studied. It is shown that the Gabierl´s thermal noise algorithm offers the best performance with respect to the number of antennas and input signal-to-noise ratio