The optimum approach to multichannel AR spectrum estimation

Abstract

A new method for multichannel autoregressive (AR) spectrum estimation is introduced based on an iterative gradient algorithm. In the context of Dynamic Programming, the method is shown to be optimum in reflection coefficient domain, whereas existing multichannel AR methods such as the Nuttall-Strand algorithm, are shown to be suboptimum. It is demonstrated that the drawbacks of the Nuttall-Strand method, namely frequency bias and line-splitting in processing sinusoidal signals, are eliminated by the optimum approach. However, the improved performance is achieved at the expense of considerably more computational effort and time.