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MMSE parameter estimation of multiple chirp signals

  • Stony Brook University

Research output: Contribution to journalConference articlepeer-review

2 Scopus citations

Abstract

We propose an iterative algorithm for minimum mean square error (MMSE) estimation of the parameters of multiple superimposed linear chirp signals in white Gaussian noise. The parameter estimation of each chirp component is carried out by two dimensional integrations. The integrals are derived with the assumption that the remaining chirp signals have parameters whose values are fixed at their current estimates. The necessary parameter initializations are obtained by tracking the Choi-Williams time-frequency distribution and applying the least-squares method. Computer simulations provide a comparison between our scheme and the alternating projection (AP) method.

Original languageEnglish
Pages (from-to)2606-2609
Number of pages4
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume5
StatePublished - 1996
EventProceedings of the 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP. Part 1 (of 6) - Atlanta, GA, USA
Duration: May 7 1996May 10 1996

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