Modified rao test for multichannel adaptive signal detection

Jun Liu, Weijian Liu, Bo Chen, Hongwei Liu, Hongbin Li, Chengpeng Hao

Research output: Contribution to journalArticlepeer-review

69 Scopus citations

Abstract

The problem of detecting a subspace signal is studied in colored Gaussian noise with an unknown covariance matrix. In the subspace model, the target signal belongs to a known subspace, but with unknown coordinates. We first present a new derivation of the Rao test based on the subspace model, and then propose a modified Rao test (MRT) by introducing a tunable parameter. The MRT is more general, which includes the Rao test and the generalized likelihood ratio test as special cases. Moreover, closed-form expressions for the probabilities of false alarm and detection of the MRT are derived, which show that the MRT bears a constant false alarm rate property against the noise covariance matrix. Numerical results demonstrate that the MRT can offer the flexibility of being adjustable in the mismatched case where the target signal deviates from the presumed signal subspace. In particular, the MRT provides better mismatch rejection capacities as the tunable parameter increases.

Original languageEnglish
Article number7299689
Pages (from-to)714-725
Number of pages12
JournalIEEE Transactions on Signal Processing
Volume64
Issue number3
DOIs
StatePublished - 1 Feb 2016

Keywords

  • Adaptive detection
  • Rao test
  • constant false alarm rate
  • mismatched signal rejection
  • subspace signal detection

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