TY - GEN
T1 - Semi-physical research for INS/GPS integrated navigation
AU - Li, Guangxin
AU - Chen, Jiabin
PY - 2013
Y1 - 2013
N2 - Inertial navigation system (INS) has a fatal flaw that positioning accuracy deteriorates with time due to possible inherent sensor errors. In order to improve the accuracy and reliability of navigation, INS/GPS system integrated with position and velocity is proposed. Core to integrated navigation systems is the concept of fusing noisy observations from GPS, Inertial Measurement Units (IMU), and other available sensors. Unscented Kalman Filter (UKF) is a filtering algorithm suitable for combining the sensor measurements with predictions coming from nonlinear models of vehicle motion. The filter has the advantages of high accuracy and reliability, and it doesn't need to linearize the nonlinear model. A semi-physical experiment research platform is used to demonstrate the results. The results significantly demonstrate the superiority of the integrated navigation and the performance of UKF-based navigation system is superior to that of the system based traditional Kalman filter on accuracy and reliability.
AB - Inertial navigation system (INS) has a fatal flaw that positioning accuracy deteriorates with time due to possible inherent sensor errors. In order to improve the accuracy and reliability of navigation, INS/GPS system integrated with position and velocity is proposed. Core to integrated navigation systems is the concept of fusing noisy observations from GPS, Inertial Measurement Units (IMU), and other available sensors. Unscented Kalman Filter (UKF) is a filtering algorithm suitable for combining the sensor measurements with predictions coming from nonlinear models of vehicle motion. The filter has the advantages of high accuracy and reliability, and it doesn't need to linearize the nonlinear model. A semi-physical experiment research platform is used to demonstrate the results. The results significantly demonstrate the superiority of the integrated navigation and the performance of UKF-based navigation system is superior to that of the system based traditional Kalman filter on accuracy and reliability.
KW - INS/GPS
KW - Kalman filter
KW - Semi-physical research
KW - UKF
UR - http://www.scopus.com/inward/record.url?scp=84886419010&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-34522-7_31
DO - 10.1007/978-3-642-34522-7_31
M3 - Conference contribution
AN - SCOPUS:84886419010
SN - 9783642345210
T3 - Lecture Notes in Electrical Engineering
SP - 281
EP - 289
BT - Proceedings of the 2012 International Conference on Information Technology and Software Engineering - Information Technology and Computing Intelligence, ITSE 2012
T2 - 2012 International Conference on Information Technology and Software Engineering, ITSE 2012
Y2 - 8 December 2012 through 10 December 2012
ER -