A Non-Convex Approach to Joint Sensor Calibration and Spectrum Estimation

Myung (Michael) Cho, Wenjing Liao, Yuejie Chi

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

1 Citation (Scopus)

Abstract

Blind sensor calibration for spectrum estimation is the problem of estimating the unknown sensor calibration parameters as well as the parameters-of-interest of the impinging signals simultaneously from snapshots of measurements obtained from an array of sensors. In this paper, we consider blind phase and gain calibration (BPGC) problem for direction-of-arrival estimation with multiple snapshots of measurements obtained from an uniform array of sensors, where each sensor is perturbed by an unknown gain and phase parameter. Due to the unknown sensor and signal parameters, BPGC problem is a highly nonlinear problem. Assuming that the sources are uncorrelated, the covariance matrix of the measurements in a perfectly calibrated array is a Toeplitz matrix. Leveraging this fact, we first change the nonlinear problem to a linear problem considering certain rank-one positive semidefinite matrix, and then suggest a non-convex optimization approach to find the factor of the rank-one matrix under a unit norm constraint to avoid trivial solutions. Numerical experiments demonstrate that our proposed non-convex optimization approach provides better or competitive recovery performance than existing methods in the literature, without requiring any tuning parameters.

Original languageEnglish (US)
Title of host publication2018 IEEE Statistical Signal Processing Workshop, SSP 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages398-402
Number of pages5
ISBN (Print)9781538615706
DOIs
StatePublished - Aug 29 2018
Event20th IEEE Statistical Signal Processing Workshop, SSP 2018 - Freiburg im Breisgau, Germany
Duration: Jun 10 2018Jun 13 2018

Publication series

Name2018 IEEE Statistical Signal Processing Workshop, SSP 2018

Conference

Conference20th IEEE Statistical Signal Processing Workshop, SSP 2018
CountryGermany
CityFreiburg im Breisgau
Period6/10/186/13/18

Fingerprint

Calibration
sensors
Sensors
matrices
optimization
Direction of arrival
Covariance matrix
norms
arrivals
estimating
Tuning
recovery
tuning
Recovery
Experiments

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Instrumentation
  • Computer Networks and Communications

Cite this

Cho, M. M., Liao, W., & Chi, Y. (2018). A Non-Convex Approach to Joint Sensor Calibration and Spectrum Estimation. In 2018 IEEE Statistical Signal Processing Workshop, SSP 2018 (pp. 398-402). [8450691] (2018 IEEE Statistical Signal Processing Workshop, SSP 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SSP.2018.8450691
Cho, Myung (Michael) ; Liao, Wenjing ; Chi, Yuejie. / A Non-Convex Approach to Joint Sensor Calibration and Spectrum Estimation. 2018 IEEE Statistical Signal Processing Workshop, SSP 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 398-402 (2018 IEEE Statistical Signal Processing Workshop, SSP 2018).
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Cho, MM, Liao, W & Chi, Y 2018, A Non-Convex Approach to Joint Sensor Calibration and Spectrum Estimation. in 2018 IEEE Statistical Signal Processing Workshop, SSP 2018., 8450691, 2018 IEEE Statistical Signal Processing Workshop, SSP 2018, Institute of Electrical and Electronics Engineers Inc., pp. 398-402, 20th IEEE Statistical Signal Processing Workshop, SSP 2018, Freiburg im Breisgau, Germany, 6/10/18. https://doi.org/10.1109/SSP.2018.8450691

A Non-Convex Approach to Joint Sensor Calibration and Spectrum Estimation. / Cho, Myung (Michael); Liao, Wenjing; Chi, Yuejie.

2018 IEEE Statistical Signal Processing Workshop, SSP 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 398-402 8450691 (2018 IEEE Statistical Signal Processing Workshop, SSP 2018).

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

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Cho MM, Liao W, Chi Y. A Non-Convex Approach to Joint Sensor Calibration and Spectrum Estimation. In 2018 IEEE Statistical Signal Processing Workshop, SSP 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 398-402. 8450691. (2018 IEEE Statistical Signal Processing Workshop, SSP 2018). https://doi.org/10.1109/SSP.2018.8450691