Frequency domain blind MIMO system identification based on second- and higher order statistics

Binning Chen, Athina P. Petropulu

Research output: Contribution to journalArticlepeer-review

114 Scopus citations

Abstract

We present a novel frequency-domain framework for the identification of a multiple-input multiple-output (MIMO) system driven by white, mutually independent, unobservable inputs. The system frequency response is obtained based on singular value decomposition (SVD) of a matrix constructed based on the power-spectrum and slices of polyspectra of the system output. By appropriately selecting the polyspectra slices, we can create a set of such matrices, each of which could independently yield the solution, or they could all be combined in a joint diagonalization scheme to yield a solution with improved statistical performance. The freedom to select the polyspectra slices allows us to bypass the frequency-dependent permutation ambiguity that is usually associated with frequency domain SVD, while at the same time allows us compute and cancel the phase ambiguity. An asymptotic consistency analysis of the system magnitude response estimate is performed.

Original languageEnglish (US)
Pages (from-to)1677-1688
Number of pages12
JournalIEEE Transactions on Signal Processing
Volume49
Issue number8
DOIs
StatePublished - Aug 2001
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Electrical and Electronic Engineering

Keywords

  • Higher order statistics
  • Joint diagonalization
  • MIMO system identification
  • Permutation ambiguity

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