The integration of GNSS RTK and IMU with extended particle filter

Abstract

Global navigation satellite system is now widely applied for various applications. For high accuracy requirements such as surveying and mobile mapping system, real time kinematic positioning (GNSS RTK) is commonly used. In the open sky, GNSS RTK can achieve centimeter level of accuracy in case of RTK fixed solution. However, in the GNSS denied or noisy environment such asunder tree canopy or under bridge, GNSS RTK accuracy becomes worse. To overcome this issue, this study applies an integrated system consisting of an GNSS RTK module and Inertial Measurement Unit (IMU) to continuously provide navigation solutions including position, velocity, and attitude. For data fusion, Extended Particle Filter (EPF) is used in this research. EPF is considered as a hybrid estimation strategy to overcome the limitations of Extended Kalman Filter, that is popularly used in data fusion. The experimental results indicated the benefit of the integrated system, particularly in the GNSS hostile environment. In addition, the testing result illustrated that the performance of EPF is significant compared to that of EKF.