A GNSS/INS Integrated Navigation Algorithm Based on Kalman Filter

Abstract

GNSS/INS (Global Navigation Satellite System/ Inertial Navigation System) integrated navigation system can be applied to agricultural UAV (unmanned aerial vehicle) with the following two requirements: (1) After working for a long time, the precision of navigation parameters will not decrease; (2) The integrated navigation algorithm is simple and reliable, which requires low processing capacity for airborne chips. Aiming at satisfying above two requirements, firstly, the centralized Kalman filter method is used to fuse GPS (Global Position System) and INS systems under the premise of loose coupling. The combination is compact, which greatly reduces the amount of computing in the system and simplifies the complexity of the system. Secondly, the error of INS system navigation parameters estimated by discrete Kalman filter algorithm is fed back into INS system by feedback emendation method, which overcomes the problem that the navigation accuracy will decline after long time work. Finally, the simulations of velocity and position error after filtering are demonstrated respectively. The stability and effectiveness of proposed algorithms are verified.