Data fusion for a GPS/INS tightly coupled positioning system with equality and inequality constraints using an aggregate constraint unscented Kalman filter
Hang Yu, Zengke Li, Jian Wang, Houzeng Han · Journal of Spatial Science · 2018
It is well known that the unscented Kalman filter (UKF) has been successfully implemented for the integration of inertial and global positioning system (GPS) measurements. This paper proposes combining an aggregate constraint method with the UKF to solve the GPS/inertial navigation system (INS) integration with equality and inequality constraints. The proposed algorithm comprehensively combines the characteristics of the aggregate constraint method and the UKF, and achieves the results in a computationally efficient way. A numerical example shows the proposed algorithm avoids large computational expense and can achieve the same level of good applicability compared with the existing constrained Kalman filter.