SYNTHESIS OF CORRELATED MULTICHANNEL RANDOM-PROCESSES

This paper describes a method for synthesizing multichannel autoregres sive (AR) random processes. The procedure allows for the variation of temporal and cross-channel correlation subject to specific constraints for correlation functions. The resulting synthesized processes provid e a ''fit'' in a minimum mean squared error (MMSE) sense to the proces s correlation functions specified in terms of their temporal and cross -channel correlation parameters. Computer simulation results are prese nted showing the case of a two-channel AR process with various values of temporal and cross-channel correlation. A method is also suggested to synthesize a more general class of Gaussian processes with unconstr ained quadrature components.