BDS/GPS Multi-System Positioning based on Nonlinear Filter Algorithm

Authors

  • Jae Hyok Kong

  • Xuchu Mao

Keywords:

global navigation satellite system (GNSS), positioning algorithm, unscented kalman filter (UKF), beidou navigation system (BDS)

Abstract

The Global Navigation Satellite System can provide all-day three-dimensional position and speed information. Currently, only using the single navigation system cannot satisfy the requirements of the system's reliability and integrity. In order to improve the reliability and stability of the satellite navigation system, the positioning method by BDS and GPS navigation system is presented, the measurement model.and the state model are described. Furthermore, Unscented Kalman Filter (UKF) is employed in GPS and BDS conditions, and analysis of single system/multi-systems2019; positioning has been carried out respectively. The experimental results are compared with the estimation results, which are obtained by the iterative least square method and the extended Kalman filtering (EFK) method. It shows that the proposed method performed high-precise positioning. Especially when the number of satellites is not adequate enough, the proposed method can combine BDS and GPS systems to carry out a higher positioning precision.

How to Cite

Jae Hyok Kong, & Xuchu Mao. (2016). BDS/GPS Multi-System Positioning based on Nonlinear Filter Algorithm. Global Journal of Computer Science and Technology, 16(G1), 9–15. Retrieved from https://computerresearch.org/index.php/computer/article/view/1418

BDS/GPS Multi-System Positioning based on Nonlinear Filter Algorithm

Published

2016-01-15