Effect of Carouseling on Angular Rate Sensor Error Processes

Abstract

Carouseling is an efficient method to mitigate the measurement errors of inertial sensors, particularly microelectromechanical systems (MEMS) gyroscopes. In this paper, the effect of carouseling on the most significant stochastic error processes of an MEMS gyroscope, i.e., additive bias, white noise, 1/f noise, and rate random walk (RRW) is investigated. Variance propagation equations for these processes under averaging and carouseling are defined. Furthermore, a novel approach to generating 1/f noise is presented. The experimental results show that carouseling reduces the contributions of additive bias, 1/f noise, and RRW significantly compared with plain averaging, which can be used to improve the accuracy of dead reckoning systems.