Research of Improved EEMD Algorithm for Timedomain Airborne Electromagnetic Signal Denoising

Common noise reduction methods need to artificially adjust the parameters according to the noise situation when applied to time domain airborne electromagnetic noise reduction,adaptability was poor. The ensemble empirical mode decomposition (EEMD) has good adaptive characteristic for nonlinear, nonstationary signal processing,the traditional signal denoising method based on EEMD reconstructed the denoised singal by combining the lowfrequency components and filtering out the highfrequency components, this approach was easily losing effective signal in highfrequency components. This paper proposed an improved EEMD noise reduction method, applied to the timedomain airborne electromagnetic signal processing. This method combined with the attenuation characteristics of the timedomain airborne electromagnetic signal,decomposed the signal into intrinsic mode function which contains signal and noise by EEMD, then through the SavitzkyGolay smoothing filtered and threshold denoised the high frequency part, finally reconstructed the denoised signal by the clear Imf components. Experimental results show that in the case of the input signal noise ratio less than or equal 15 dB,the output signal noise ratio can be increased by about 12 dB, this approach not only reduces noise but also retains information more effectively.