Low-angle tracking of two objects in a three-dimensional beamspace domain

Abstract

Among various low-angle tracking methods, the three-dimensional beamspace domain maximum likelihood (3-D BDML) estimation proposed by Zoltowski is a computationally attractive and optimal method that can be processed in the reduced beamspace domain. However, the estimation performance of 3-D BDML deteriorates in the presence of interference or an additional target, especially at low altitudes, because the dimension of the signal and noise exceeds the dimension provided by the three beams. This study proposes a new low-angle tracking method for two objects in a 3-D beamspace domain using a linearly constrained adaptive array. The increased signal dimension owing to the interference or the additional target is reduced in the beamspace domain by using the beamforming weight that is designed to remove the largest principal component in the covariance matrix. Numerical simulation results are provided to show the estimation performance of the proposed method.