Synthesis of correlated multichannel random processes

Author

Michels, James H. ; Varshney, Pramod K. ; Weiner, Donald D.

Author_Institution

Rome Lab., Griffiss AFB, NY, USA

Volume

42

Issue

2

fYear

1994

fDate

2/1/1994 12:00:00 AM

Firstpage

367

Lastpage

375

Abstract

This paper describes a method for synthesizing multichannel autoregressive (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 provide a “fit” in a minimum mean squared error (MMSE) sense to the process correlation functions specified in terms of their temporal and cross-channel correlation parameters. Computer simulation results are presented 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 unconstrained quadrature components

Keywords

approximation theory; correlation theory; random processes; signal detection; signal synthesis; stochastic processes; time series; AR random processes; Gaussian processes; MMSE; autoregressive processes; computer simulation; correlated multichannel random processes; correlation functions; cross-channel correlation; minimum mean squared error; synthesis method; temporal correlation; unconstrained quadrature components; Computer errors; Computer simulation; Filtering theory; Gaussian processes; Random processes; Reverberation; Signal processing; Signal synthesis; Signal to noise ratio; White noise;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.275609

Filename

275609