Signal characterization effect on adaptive superresolution algorithms

In this paper, we examine a high resolution direction of arrival (DOA) estimation techniques. Among these algorithms which can yield accurate DOA estimates for multiple narrow band sources are Gabierl's thermal noise, adaptive angular response, and maximum-likelihood method. These algorithms are capable of detecting pulses that exist for short periods of time. Under this environment, the performance of different adaptive superresolution array algorithms that utilize the Howell-Applebaum technique is compared. Two different cases are discussed. Firstly, the adaptive array is subjected to only one signal plus thermal noise. Secondly, the case of the presence of two incident signals plus thermal noise is investigated. It is shown that every algorithm offers its best performance depending upon the incident signal parameters, number of antennas, the range of input signal-to-noise ratio, and the angle of separation between the incoming signals.