Extracting and compensating for FOG vibration error based on improved empirical mode decomposition with masking signal.

Vibration is an important error source in fiber-optic gyroscopes (FOGs), and the extraction and compensation of vibration signals are important ways to eliminate the error and improve the accuracy of FOG. To decompose the vibration signal better, a new algorithm based on empirical mode decomposition (EMD) with masking signal is proposed in this paper. The masking signal is a kind of sinusoidal signal, and the frequency and amplitude of the masking signal are selected using improved particle swarm optimization. The proposed algorithm is called adaptive masking EMD (AM-EMD). First, the optimal frequency value and range of the masking signal are analyzed and presented. Then, an optimal decomposition of the vibration signal is obtained using the PSO to obtain the optimal frequency and amplitude of the masking signal. Finally, the extraction and compensation of the vibration signal are completed according to the mean value of intrinsic mode functions (IMFs) and the correlation coefficients between IMFs and the vibration signal. Experiments show that the new method can decompose the signal more accurately compared to traditional methods, and the precision of compensation is higher.