Iterative deconvolution algorithm of blind equalization for MEMS gyroscope signal

The mathematical model of a mobile mini-robot running in unknown environment cannot be effectively built due to gyroscope's noise interference, and needs to remove the noise only from the observing signal and estimate the original signal. In this paper, an iterative deconvolution algorithm of blind equalization for MEMS gyroscope signal is presented. The transversal filter for the gyroscope signal to implement deconvolution calculation is employed, and the signal is estimated by Bayesian methods. The error function is established and combined with LMS algorithm to achieve the automatic adjustment of equalization parameter. The verification of the algorithm is carried out on the mini-mobile robot. The experiment results show that the angular velocity and noise signals can be effectively extracted from the mixed signals, and the amplitude of noise signal is decreased to about 1/10 of the original. After the mobile robot has run 275.41 s, the error of its final yaw angle for mobile robot is reduced from 13° to 1.46°.