Abstract
In a Non-gyro micro inertial measurement unit (NGMIMU) system, an inevitable accumulation error of navigation parameters is produced due to the existence of the dynamic noise of the accelerometer output. When designing an integrated navigation system which is based on a nine-configuration NGMIMU and a single antenna Global Positioning System (GPS) by using the conventional Kalman filter (CKF), the filtering results are divergent because of the complicity of the system measurement noise. So a self-adaptive Kalman filter (SAKF) is applied in the design of NGMIMU/GPS to solve the uncertainty of the statistical characteristics of the two noises above. This filtering approach optimizes the filter by judging the prediction residuals of the filtering and calculating the statistical characteristics of the noises by using the maximum a posterior estimator. A simulation case for estimating the position, velocity and angle rate is investigated by this approach. Results verify the feasibility of the SAKF.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
