Affiliation:
1. Software and Service Outsourcing Institute, Suzhou Vocational Institute of Industrial Technology, Suzhou 215000, China
2. School of Management Science & Industrial, Nanjing University of Finance and Economics, Nanjing 210023, China
3. AVIC Beijing Keeven Aviation Instrument Co., Ltd, Beijing 100086, P. R. China
Abstract
The accuracy of attitude and heading measurement, as well as the system real-time performance are basic indicators used to evaluate an attitude and heading reference system (AHRS). In order to improve the attitude and heading measurement accuracy under dynamic complex environment, the AHRS system should also have numerical stability and calculation robustness. The AHRS system based on MEMS multi-sensor fusion can realize fusion processing of data measured by multiple sensors, so as to calculate and obtain the optimal carrier attitude and heading information, conduct real-time output, and improve the accuracy and reliability of attitude and heading measurement. For the AHRS system consisting of MEMS gyroscope, accelerometer and triaxial magnetometer, attitude and heading detection principle and algorithm based on MEMS multi-sensor fusion were proposed in this study: The information of the system itself was firstly used to discriminate motion state of the carrier within the filtering cycle, and then Kalman filtering was conducted using different measured information according to motion state to correct the attitude error angle caused by gyroscopic drift. On this basis, an attitude fusion algorithm based on extended Kalman filtering technology was designed for time update process of Kalman filtering, output information of accelerometer was taken as observed quantity under certain conditions to realize measurement updating process of Kalman filtering, and then attitude angle was calculated. In an optical fiber attitude and heading system project in practical engineering, a vehicle field test analysis was carried out simultaneously with the system using ordinary attitude algorithm, and the results showed that the extended Kalman filtering algorithm designed according to the simulation results could realize multi-sensor information fusion, improve measurement accuracy and realize accurate attitude positioning, so as to provide simpler and more flexible criteria for carrier motion status. The results have verified the accuracy and reliability of the algorithm, so it is feasible in practical engineering.
Funder
National Natural Science Foundation of China
Practical Training Project for Young Teachers in Higher Vocational Colleges of Jiangsu Province
Nanjing University of Finance and Economics Institute of Higher Education 2019 School-level Teaching Reform
Publisher
World Scientific Pub Co Pte Lt
Subject
Artificial Intelligence,Information Systems,Control and Systems Engineering,Software
Cited by
11 articles.
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