A highly adaptable method for GNSS cycle slip detection and repair based on Kalman filter

Abstract

The cycle slip detection and repair are crucial steps in the preprocessing of GNSS carrier phase observation. Currently, however, there are few cycle slip detection and repair methods that can meet the data processing needs for diverse situations. To solve this problem, a highly adaptable cycle slip detection and repair method is proposed. First, a cycle slip detection equation is established using the pseudo-range and carrier double-differenced (DD) observations; the state equation is developed based on the satellite-ground distance. Then, a Kalman filter estimation model is established by joining the two equations. Subsequently, the cycle slip can be detected and repaired. Finally, the state parameters are refined in accordance with the conditional distribution. According to the results of the example, all the simulated cycle slips are detected and repaired by the method proposed. It shows that the method can meet the data processing needs for multiple situations.

Keywords:

• GNSS
• Cycle slip detection and repair
• Highly adaptable
• Kalman filter
• LAMBDA

Acknowledgements

This research was funded by the National Natural Science Foundation of China, grant number: 41974030 and 41674035.

Notes on contributor

Xianwen Yu is currently an associate professor in the School of Transportation, Southeast University in Nanjing, China. He received his Ph.D. degree in Precision Instrument and Machinery from Southeast University in 2009. His current research interest is in GNSS precise positioning algorithms.

Siqi Xia is a master student in School of Transportation, Southeast University in Nanjing, China. His current research interests include cycle slip detection and high precision GNSS data processing.

Additional information

Funding

This work was supported by National Natural Science Foundation of China: [Grant Number 41674035]; [Grant Number 41974030].