Journal of Jilin University(Earth Science Edition) ›› 2016, Vol. 46 ›› Issue (3): 876-883.doi: 10.13278/j.cnki.jjuese.201603301

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Application of Minimum Noise Fraction on Noise Removal for Airborne Electromagnetic Data

Zhu Kaiguang, Li Yue, Meng Yang, Wang Lingqun, Xie Bin, Cheng Yuqi   

  1. College of Instrumentation and Electrical Engineering, Jilin University/Key Laboratory of Geo-Exploration Instrumentation, Ministry of Education, Changchun 130026, China
  • Received:2015-10-15 Online:2016-05-26 Published:2016-05-26
  • Supported by:

    Supported by the National High-Tech R & D Program of China (2013AA063904), the National Natural Science Foundation of China (41274076) and R & D of Key Instruments and the National R & D Projects for Key Scientific Instrumentsof China(ZDYZ2012-1-03)

Abstract:

There is still residual noise in time-domain airborne electromagnetic data after preprocessing, which will affect the recognition of target. We proposed an approach to remove the residual noise based on minimum noise fraction. A set of noise-contaminated data will be linearly transformed by using the rotation matrix to the minimum noise fraction components, which are arranged in signal to noise ratio (SNR) from big to small. We use the minimum noise fraction components with the bigger SNR to reconstruct the electromagnetic data for separating the signal and noise.The experiment with the simulation data test shows that the minimum noise fraction can not only effectively suppress the noise of the profile of later channels, but also accurately identify the information of the target. The SNR has improved by 11.28 dB compared with the survey-line filtering. The noise level for the field data is reduced from ±50 nT/s to ±10 nT/s after noise removal.

Key words: time-domain airborne electromagnetic data, minimum noise fraction, noise removal, survey-linefiltering

CLC Number: 

  • P631.2

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