Off-Grid Chirp-Rate Estimation for LFM Signals Based on Dynamic Dictionary

Yue Ma*, Yan Liu, Qing Shen

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Under the compressive sensing (CS) framework, a chirp-rate estimation method for multi-component linear frequency modulation (LFM) signals in the off-grid case is proposed, where the chirp-rates and the corresponding off-grid bias terms are estimated separately for complexity reduction. Then, an iterative off-grid chirp-rate estimation method based on dynamic dictionary is presented, where the estimated chirp-rates are iteratively employed to generate the extremely sparse dictionary. Improved estimation accuracy is achieved by alleviating the offgrid approximation error gradually, and the complexity caused by the iterations is limited due to the small number of parameters to be optimized (equal to the number of signals).

Original languageEnglish
Title of host publication2023 6th International Conference on Electronics Technology, ICET 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1340-1344
Number of pages5
ISBN (Electronic)9798350337693
DOIs
Publication statusPublished - 2023
Event6th International Conference on Electronics Technology, ICET 2023 - Chengdu, China
Duration: 12 May 202315 May 2023

Publication series

Name2023 6th International Conference on Electronics Technology, ICET 2023

Conference

Conference6th International Conference on Electronics Technology, ICET 2023
Country/TerritoryChina
CityChengdu
Period12/05/2315/05/23

Keywords

  • LFM signals
  • Taylor expansion
  • chirp-rate estimation
  • compressive sensing
  • off-grid

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