Application of RPF in MEMS gyro random drift filtering

Abstract

With the development of micro-mechanical inertial technology, how to suppress the MEMS gyro’s random drift increasingly become a hot topic. In order to filter a certain type of MEMS gyro’s random drift, this paper introduces the regularized particle filter algorithm. The derivation of the algorithm and its application in MEMS gyro’s filtering process are described in detail in this paper: First, acquiring MEMS gyro’s static drift data and conducting data pre-treatment; then establishing the AR model by using time series analysis method, and transforming it into the corresponding state space model; finally, executing the estimation and compensation for MEMS gyro’s random drift with regular particle filter algorithm, and comparing it with other common methods in engineering. Tests and simulation results show that the regularized particle filter algorithm could achieve a good effect on the suppression of MEMS gyro’s random drift, it has a higher practical application value.