A multi-MEMS sensors information fusion algorithm

With the development of new technologies and changes in market demand, MEMS gyroscope is widely used, but the low accuracy, large drift and other defects limit their application in some areas. This paper presents a Kalman filter-based multi-sensor fusion algorithm to improve the positioning and tracking accuracy of MEMS devices. The technology of multi-sensor information fusion has been put into use in the military defense and other fields. Information fusion can obtain a more precise system estimate on the basis of multiple independent data. There are many methods of information fusion, of which Kalman filter is the most popular. The multi-sensor information fusion on the basis of Kalman filter focus on measuring integration and state integration. The paper firstly introduces the fundamental models of Kalman filter algorithm, and then puts forward the two improved algorithm. With the advantages of these two methods, a new fusion algorithm has come out, and simulation verification has been designed. The results show that, the proposed fusion algorithm can improve the fusion accuracy and ensure the stability, so that help MEMS devices to satisfy the demands of practical applications.