학술논문

Joint Calibration and Tomography based on Separable Least Squares Approach with Constraints on Linear and Non-Linear Parameters
Document Type
Conference
Source
2020 28th European Signal Processing Conference (EUSIPCO) European Signal Processing Conference (EUSIPCO), 2020 28th. :1931-1935 Jan, 2021
Subject
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineering Profession
Signal Processing and Analysis
Temperature measurement
Jacobian matrices
Temperature distribution
Tomography
Position measurement
Time measurement
Calibration
online sensor calibration
constrained optimization
Language
ISSN
2076-1465
Abstract
Most of the existing tomography techniques rely on accurate calibration to reconstruct the features of interest. In several industrial applications, the calibration is typically performed off-line and has to be repeated frequently to counter time varying perturbation caused by aging, operating conditions, and so on. In this paper, a novel online joint calibration and tomography method based on variable projection based separable least squares approach with constraints on linear and non-linear parameters is proposed. The constraints on the linear parameters improve the estimation accuracy of the ill-posed and under determined tomography problem. The constraints on the non-linear parameters restricts the proposed method from departing far away from the initial guess, especially when a good initial guess is available. The proposed method is used to reconstruct the temperature distribution inside a blast furnace and simultaneously to calibrate the positions of acoustic transducers based on simulated acoustic time of flight measurements.