Error Self-Calibration Algorithm for Acoustic Vector Sensor Array

Wang, Peng; Kong, Yujun; Zhang, Mingxing

doi:10.1155/2019/9052547

Cited by 1 publication

(1 citation statement)

References 14 publications

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“…However, it is difficult to establish a corresponding mathematical model for nonlinear systems. Wang, Kong [13], and others classified the errors of the acoustic vector sensor array and designed an optimization model and error selfcalibration algorithm for the acoustic vector sensor array. This algorithm can perform quite well in parameter estimation, but when the mathematical model is established, the iterative calculation of coefficients still needs much work.…”

Section: Introductionmentioning

confidence: 99%

A Nonlinear Calibration Method Based on Sinusoidal Excitation and DFT Transformation for High‐Precision Power Analyzers

et al. 2021

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For most high-precision power analyzers, the measurement accuracy may be affected due to the nonlinear relationship between the input and output signal. Therefore, calibration before measurement is important to ensure accuracy. However, the traditional calibration methods usually have complicated structures, cumbersome calibration process, and difficult selection of calibration points, which is not suitable for situations with many measurement points. To solve these issues, a nonlinear calibration method based on sinusoidal excitation and DFT transformation is proposed in this paper. By obtaining the effective value data of the current sinusoidal excitation from the calibration source, the accurate calibration process can be done, and the calibration efficiency can be improved effectively. Firstly, through Fourier transform, the phase value at the initial moment of the fundamental frequency is calculated. Then, the mapping relationship between the sampling value and the theoretical calculation value is established according to the obtained theoretical discrete expression, and a cubic spline interpolation method is used to further reduce the calibration error. Simulations and experiments show that the calibration method presented in this paper achieves high calibration accuracy, and the results are compensation value after calibration with a deviation of ± 3 × 10 − 4 .

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Section: Introductionmentioning

confidence: 99%