Estimation of chirp signals with time-varying amplitudes

Research output: Contribution to journalArticle

Abstract

The problem of parameters estimation of signals composed of an unknown number of chirps with time-varying amplitude is presented using a sparse reconstruction framework. The method employs a parametric model using a weighted combination of splines to model the time-varying nature of the signal amplitudes. To obtain high-resolution of the frequencies and to avoid large dimensional matrices, a dictionary refinement technique is employed. The method can accurately estimate the amplitude and frequency parameters of multiple signal components, and may be extended to allow for non-linear chirps. Furthermore, an efficient implementation to solve the resulting optimization problem is proposed. Results on both synthetic and experimental signals illustrate the efficient performance of the algorithm.

Details

Authors
Organisations
External organisations
  • Harbin Engineering University
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Signal Processing

Keywords

  • ADMM, Chirp signals, Sparse reconstruction, Time-varying amplitude
Original languageEnglish
Pages (from-to)1-10
Number of pages10
JournalSignal Processing
Volume147
Publication statusPublished - 2018 Jun 1
Publication categoryResearch
Peer-reviewedYes