Research on Optical Fiber IMU Signal Processing Based on Wavelet Algorithm
Xiaogong Lin, Ruxin Guo, Yuqi Yuan · 2019
Based on the analysis of the signal noise characteristics of inertial navigation accelerometer, the noise in the wavelet domain is deeply studied. In order to solve the limitation of traditional Fourier filtering method in dealing with non-linear noise such as Gauss white noise, this paper optimizes the existing wavelet theory from two aspects of threshold estimation and threshold processing function, and proposes a new wavelet threshold denoising algorithm, which can effectively improve the performance of wavelet algorithm and simplify the calculation of wavelet analysis; on this basis, a new wavelet threshold denoising algorithm is proposed. The implementation of the wavelet threshold algorithm on the FPGA is studied. Finally, the system performance test shows that the new wavelet algorithm is superior to the traditional Fourier filter and the traditional wavelet filter in improving the signal-to-noise ratio (SNR) and reducing the root mean square error, and meets the real-time requirements of signal processing.