WANG Hongwei, ZHANG Wei, ZUO Junyi, WANG Heping. Frequency and Offset Online Estimation of Sinusoidal Signals Based on High-Order Nonlinear Continuous Differentiator[J]. Chinese Journal of Electronics, 2017, 26(3): 579-584. doi: 10.1049/cje.2017.01.007
Citation: WANG Hongwei, ZHANG Wei, ZUO Junyi, WANG Heping. Frequency and Offset Online Estimation of Sinusoidal Signals Based on High-Order Nonlinear Continuous Differentiator[J]. Chinese Journal of Electronics, 2017, 26(3): 579-584. doi: 10.1049/cje.2017.01.007

Frequency and Offset Online Estimation of Sinusoidal Signals Based on High-Order Nonlinear Continuous Differentiator

doi: 10.1049/cje.2017.01.007
Funds:  This work is supported by the National Natural Science Foundation of China (No.61473227, No.11472222), the Aerospace Technology Support Fund of China (No.2014-HT-XGD), the Natural Science Foundation of Shaanxi Province, China (No.2015JM6304), and the Aeronautical Science Foundation of China (No.20151353018).
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  • Corresponding author: ZHANG Wei (corresponding author) was born in 1963. He received the B.S/M.S degrees in flight mechanics and Ph.D. degree in aircraft design from Northwestern Polytechnical University. He was invited as associate professor in the School of Creative Media, City University of Hong Kong during 2013-2014. (Email:weizhangxian@nwpu.edu.cn)
  • Received Date: 2015-08-09
  • Rev Recd Date: 2016-07-13
  • Publish Date: 2017-05-10
  • Real-time parameter identification of sinusoidal signals is an essential research topic due to its broad utilization in both theoretical studies and engineering practice. A tracking differentiator based online estimation framework has been proposed to simultaneously identify frequencies and offset of given multi-sinusoidal signal. Tracking differentiator is exploited in presented framework to track the time derivatives of measurements which are then utilized to estimate the frequencies and offset. We introduce a tracking differentiator called high-order nonlinear continuous differentiator into the framework, giving birth to a new estimation algorithm. Comparative experiments on both single and two sinusoidal signal are simulated, indicating the superiority of proposed method on both convergent speed and estimation accuracy.
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