摘要：AbstractGyroscopes are physical sensors that detect and measure the angular motion of an object relative to an inertial frame of reference. The low cost MEMS gyroscopes are known to have a smaller size, lower weight and less power consumption than their discrete counterparts. However the current state-of-the-art MEMS gyroscopes have low grade performance and cannot compete with established sensors in high accuracy navigational and guidance applications. By integrating large numbers of MEMS gyroscopes on a single circuit board in a defined configuration, the collective behavior of these devices can be improved. Kalman filtering technique provides a discrete estimation algorithm to fuse the individual gyroscope outputs to a single virtual gyroscope output. The combined gyro drift is reduced and their performance is improved from low grade to high grade aiding in much wider applications.
关键词：KeywordsMEMS gyroscopeclustering of sensorsKalman filteringAngle Random Walk(ARW)Rate Random Walk(RRW)
