Comparison of the conjugate gradient method to the method of recursive least square in terms of convergence rate

The convergence speed of the conjugate gradient method (CGM) is compared to that of the Kalman method. From simulations, the required computation time of CGM is about 79%-101% of that of the Kalman method. All the parameter values are set in both methods such that the performance of the receiving array is acceptable for land mobile communications. The main factor that causes the computation time to increase in the Kalman method is updating the inverse subcorrelation matrix. The main reason the CGM is superior to conventional algorithms is that the optimal weights are obtained in P steps in any signal environment.