Title :
Adaptive Kalman filtering based navigation: An IMU/GPS integration approach
Author :
Fakharian, A. ; Gustafsson, Thomas ; Mehrfam, M.
Author_Institution :
Dept. of Electr. & Comput. Eng., Islamic Azad Univ., Qazvin, Iran
Abstract :
This paper investigates on the development and implementation of a high integrity navigation system based on the combined use of the Global Positioning System (GPS) and an inertial measurement unit (IMU) for land vehicle applications. The complementary properties of the GPS and the INS have motivated several works dealing with their fusion by using a Kalman Filter. The conventional kalman filter has a fix error covariance matrix in all times of processing. Multi-sensor based navigation system that is implemented in this paper is called data synchronization. Also, multi-rate operations that are compared with conventional Kalman filtering has fix error covariance matrix. Therefore, when GPS outage occurred we have improper treat by kalman filter. In this paper we present an Adaptive method instead of conventional methods. It is shown that proposed method has a better performance rather than conventional method. Experimental results show the effectiveness of the GPS/INS integrated system.
Keywords :
Global Positioning System; Kalman filters; covariance matrices; path planning; remotely operated vehicles; sensor fusion; synchronisation; GPS; IMU; adaptive Kalman filtering; autonomous land vehicle; data synchronization; error covariance matrix; global positioning system; inertial measurement unit; land vehicle application; multirate operation; navigation system; Accuracy; Global Positioning System; Kalman filters; Land vehicles; Sensors; Kalman filter; Land vehicle; global positioning system (GPS); inertial measurement unit (IMU); navigation;
Conference_Titel :
Networking, Sensing and Control (ICNSC), 2011 IEEE International Conference on
Conference_Location :
Delft
Print_ISBN :
978-1-4244-9570-2
DOI :
10.1109/ICNSC.2011.5874871