吉林大学学报(工学版) ›› 2016, Vol. 46 ›› Issue (3): 985-995.doi: 10.13229/j.cnki.jdxbgxb201603046

• Orginal Article • Previous Articles     Next Articles

Least-square weighted smoothing filter technology applied in magnetic resonance sounding signal processing

SUN Shu-qin1, 2, LIU Jun-yan1, 2, JIANG Chuang-dong1, 2, MENG Qing-yun1, 2, LIN Jun1, 2, PENG Liang-yu1, 2   

  1. 1.College of Instrumentation and Electrical Engineering, Jilin University, Changchun 130026, China;
    2.Laboratory of Geo-Exploration and the Instrumentation Ministry of Education of China, Jilin University, Changchun 130026, China
  • Received:2015-03-16 Online:2016-06-20 Published:2016-06-20

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Abstract: Least Square Weighted Smoothing Filter (LSW-SF) method is used to filter Magnetic Resonance Sound (MRS) signals, which is compared with the moving average filter method. Results of a large number of simulation experiments show the following characteristics. First, the more accurate characteristic parameters of MRS can be obtained using the LSW-SF method, and the Signal to Noise Ratio (SNR) is also improved. Second, the LSW-SF method is more suitable for random noise and rush noise removal. Third, appropriate weights should be chosen when the LSW-SF method is used to wipe out noise. Among them fitting error of MRS signal characteristic parameters can be controlled within 1%, and the smoothness of the signal curve is greatly improved. Meanwhile, the filter processing of the measured data indicates this method is effective.

Key words: electrical engineering, magnetic resonance sounding (MRS), data filtering, moving average, least squares

CLC Number: 

  • TN911.7
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