Title :
IM-filter for INS/GPS-integrated navigation system containing low-cost gyros
Author_Institution :
Kyungil Univ., South Korea
Abstract :
This paper proposes a new interacting multiple (IM) filter containing simplified unscented Kalman filter (UKF) -based subfilters with different heading initializations for a low-performance inertial sensors-based inertial navigation system (INS)/global positioning system (GPS) -integrated navigation system tolerant toward large initial heading error. Since each individual subfilter of the IM filter is updated adaptively using the combined information of the estimates from the subfilters, it can converge into a true steady state irrespective of the initial heading of a vehicle containing the navigation system. Thereby the IM filter can provide a stable navigation solution. For the subfilters of the IM filter, a simplified UKF is presented. This has a mixed structure of the extended Kalman filter and UKF and has a lighter computational load than the UKF in the multirate INS/GPS integration. Also, simplified UKF-based subfilters for the INS/GPS-integrated navigation system are designed. Monte Carlo simulations are performed to validate the performance of the proposed IM filter, and an experiment is carried out to confirm the simulation results.
Keywords :
Global Positioning System; Kalman filters; Monte Carlo methods; computational complexity; inertial navigation; nonlinear filters; IM filter; INS-GPS integrated navigation system; Monte Carlo simulation; UKF; computational load; extended Kalman filter; global positioning system navigation system; inertial sensors based inertial navigation system; interacting multiple filter; unscented Kalman filter; Covariance matrices; Finite impulse response filters; Global Positioning System; Kalman filters; Time measurement;
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on
DOI :
10.1109/TAES.2014.130128