2 TYPES OF ADAPTIVE BEAMFORMER USING 2-D JOINT PROCESS LATTICE ESTIMATOR

This paper presents two types of two-dimensional (2-D) adaptive beamfo rming algorithm which have high rate of convergence. One is a linearly constrained minimum variance (LCMV) beamforming algorithm which minim izes the average output power of a beamformer, and the other is a gene ralized sidelobe canceler (GSC) algorithm which generalizes the notion of a linear constraint by using the multiple linear constraints. In b oth algorithms, we apply a 2-D lattice filter to an adaptive filtering since the 2-D lattice filter provides excellent properties compared t o a transversal filter. In order to evaluate the validity of the algor ithm, we perform computer simulations. The experimental results show t hat the algorithm can reject interference signals while maintaining th e direction of desired signal, and can improve convergent performance.