Research of steepest descent and conjugate gradient in digital beamforming

In the adaptive beamforming technology,the conjugate gradient method is a common method.The steepest descent method searchs the optimum weights by iterative method without matrix reverse.In this paper,a hybrid algorithm is proposed based on the the steepest descent method and the conjugate gradient method.In each iteration,by the negative conjugate gradient search direction and the optimum adaptive step this method raises the convergence rates of the conjugate gradient and solves the problem which the convergence rates get slower with the small eigenvalue spread of the correlation matrix.In conclusion,this paper has the features with quick convergence rate,low operation.The computer simulation shows the five ULA array elements digital beamforming example,analyzes the beamforming,error convergence and the optimum weight and so on by comparing with the traditional LMS algorithm.The results indicate this method is feasibility and validity.