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Grid Evolution: An Iterative Reweighted Algorithm for Off-grid DOA Estimation with Gain/Phase Uncertainties

  • School of Electronics and Information Engineering, Harbin Institute of Technology

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

Abstract

Conventional direction-of-arrival (DOA) estimation based on compressed sensing assumes that the true DOAs are on the discretized grid. However, the accuracy of DOA estimation will deteriorate since most DOAs don't lie on the grid. This problem is also called off-grid problem or grid mismatch. Besides the grid mismatch problem, another problem should not be overlooked is the existence of the sensors imperfections, such as the gain/phase uncertainties. In order to solve these problems, an iterative reweighted-total least squares (IR-TLS) DOA estimation method based on compressed sensing (CS) is proposed. Firstly, the original problem is transformed into a total least-squares (TLS) framework. An alternating descent algorithm is then developed. The DOAs are estimated and the grid is refined through an iterative reweighted method. Then the gain/phase uncertainties are updated with the estimated DOAs and refined grid through iterations. Simulation results are provided to show that the proposed IR-TLS method can help improving the accuracy of off-grid DOA estimation with less computational complexity.

Original languageEnglish
Title of host publicationICSIDP 2019 - IEEE International Conference on Signal, Information and Data Processing 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728123455
DOIs
StatePublished - Dec 2019
Externally publishedYes
Event2019 IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2019 - Chongqing, China
Duration: 11 Dec 201913 Dec 2019

Publication series

NameICSIDP 2019 - IEEE International Conference on Signal, Information and Data Processing 2019

Conference

Conference2019 IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2019
Country/TerritoryChina
CityChongqing
Period11/12/1913/12/19

Keywords

  • Off-grid direction-of-arrival (DOA) estimation
  • compressed sensing
  • gain/phase uncertainties
  • iterative reweighted algorithm
  • total least squares

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