Isfahan University of Technology
Department of Electrical and Computer Engineering
Issue date: 4 January, 2015
Contributor: Ali Hassanipour
Supervisor: Dr. Asghar Gholami
Counselor: Dr. Habib Ghanbarpour asl
Keywords: Inertial navigation system, Loosely coupled INS/GPS integration, Particle filter, Kalman filter.
Inertial Navigation System (INS) using initial states such as initial position, attitude, velocity and measuring accelerations and rotation rates in three dimensions, estimates vehicle position, attitude and velocity. Inertial sensors usually have noises. Therefore, INS output errors increase rapidly with time.
For reducing these errors and increasing navigation accuracy, INS should be integrated with other aided navigation sensors such as Global Positioning System (GPS). One of integration types is called Loosely coupled INS/GPS integration, which has been investigated in this research. Integration needs an estimation method such as particle filters and Kalman filters used in this thesis.
In this thesis, Loosely coupled INS/GPS navigation system using particle filter is designed to reduce navigation errors. Additionally, some Kalman filters outputs have been achieved for comparison. In this research, some particle filters and Kalman filters such as SIR PF, SIS PF, error state extended Kalman filter (ESKF), total state extended Kalman filter (TSKF), error state extended particle filter (ESPF) and total state extended particle filter (TSPF) have been described and implemented. Finally, partticle filters results have been compared to Kalman filters outputs in different conditions.