@ARTICLE{Li_Zengke_Application_2017,
 author={Li, Zengke and Yao, Yifei and Wang, Jian and Gao, Jingxiang},
 volume={vol. 24},
 number={No 2},
 journal={Metrology and Measurement Systems},
 pages={289–301},
 howpublished={online},
 year={2017},
 publisher={Polish Academy of Sciences Committee on Metrology and Scientific Instrumentation},
 abstract={A robust Kalman filter improved with IGG (Institute of Geodesy and Geophysics) scheme is proposed and used to resist the harmful effect of gross error from GPS observation in PPP/INS (precise point positioning/inertial navigation system) tightly coupled positioning. A new robust filter factor is constructed as a three-section function to increase the computational efficiency based on the IGG principle. The results of simulation analysis show that the robust Kalman filter with IGG scheme is able to reduce the filter iteration number and increase efficiency. The effectiveness of new robust filter is demonstrated by a real experiment. The results support our conclusion that the improved robust Kalman filter with IGG scheme used in PPP/INS tightly coupled positioning is able to remove the ill effect of gross error in GPS pseudorange observation. It clearly illustrates that the improved robust Kalman filter is very effective, and all simulated gross errors added to GPS pseudorange observation are successfully detected and modified.},
 type={Artykuły / Articles},
 title={Application of Improved Robust Kalman Filter in Data Fusion for PPP/INS Tightly Coupled Positioning System},
 URL={http://www.journals.pan.pl/Content/107356/PDF-MASTER/146.pdf},
 doi={10.1515/mms-2017-0031},
 keywords={PPP/INS tightly coupled positioning, robust filter, IGG scheme, Mahalanobis distance},
}