Blind gain and phase calibration for low-dimensional or sparse signal sensing via power iteration

Yanjun Li, Kiryung Lee, Yoram Bresler

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Blind gain and phase calibration (BGPC) is a bilinear inverse problem involving the determination of unknown gains and phases of the sensing system, and the unknown signal, jointly. BGPC arises in numerous applications, e.g., blind albedo estimation in inverse rendering, synthetic aperture radar autofocus, and sensor array auto-calibration. In some cases, sparse structure in the unknown signal alleviates the ill-posedness of BGPC. Recently there has been renewed interest in solutions to BGPC with careful analysis of error bounds. In this paper, we formulate BGPC as an eigenvalue/eigenvector problem, and propose to solve it via power iteration, or in the sparsity or joint sparsity case, via truncated power iteration. Under certain assumptions, the unknown gains, phases, and the unknown signal can be recovered simultaneously. Numerical experiments show that power iteration algorithms work not only in the regime predicted by our main results, but also in regimes where theoretical analysis is limited. We also show that our power iteration algorithms for BGPC compare favorably with competing algorithms in adversarial conditions, e.g., with noisy measurement or with a bad initial estimate.

Original languageEnglish (US)
Title of host publication2017 12th International Conference on Sampling Theory and Applications, SampTA 2017
EditorsGholamreza Anbarjafari, Andi Kivinukk, Gert Tamberg
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages119-123
Number of pages5
ISBN (Electronic)9781538615652
DOIs
StatePublished - Sep 1 2017
Event12th International Conference on Sampling Theory and Applications, SampTA 2017 - Tallinn, Estonia
Duration: Jul 3 2017Jul 7 2017

Publication series

Name2017 12th International Conference on Sampling Theory and Applications, SampTA 2017

Other

Other12th International Conference on Sampling Theory and Applications, SampTA 2017
CountryEstonia
CityTallinn
Period7/3/177/7/17

ASJC Scopus subject areas

  • Signal Processing
  • Statistics, Probability and Uncertainty
  • Analysis
  • Statistics and Probability
  • Applied Mathematics

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    Li, Y., Lee, K., & Bresler, Y. (2017). Blind gain and phase calibration for low-dimensional or sparse signal sensing via power iteration. In G. Anbarjafari, A. Kivinukk, & G. Tamberg (Eds.), 2017 12th International Conference on Sampling Theory and Applications, SampTA 2017 (pp. 119-123). [8024422] (2017 12th International Conference on Sampling Theory and Applications, SampTA 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SAMPTA.2017.8024422