High-Precision Attitude Estimation Based on Differential IMU Array

Abstract

To solve the low precision and poor anti-interference of a single Micro-Electro-Mechanical System (MEMS) inertial sensor, this paper proposes a high-precision attitude estimation system based on differential Inertial Measurement Unit (IMU) array. Based on the output characteristics of a single MEMS inertial sensor, the output performances of the differential IMU array are analyzed, which show effectively improvements for the bias stability and random noise compared to a single MEMS inertial sensor. Moreover, the attitude estimation algorithms based on the Kalman filter and complementary filter are used to fuse data from sensors and calculate the attitude. The experimental results show that the error of angular rate of the differential IMU array is reduced by 79.7% and the standard deviation of the attitude measurement results is reduced by about 75% compared with that of a single sensor in both static state and dynamic state. The estimated absolutely roll angle and pitch angle errors are within 0.4° in dynamic state which are the state-of-the-arts results to date. This study can be effectively used to the smart and wearable devices and industrial automation in the emerging areas.