Extended Kalman Filter (EKF) Innovation-based Integrity Monitoring Scheme with C/N0 Weighting

IEEE RTSI 2018, 4th International Forum on Research and Technologies for Society and Industry, Palerme, ITALIE, 10-/09/2018 - 13/09/2018; Global Navigation Satellite Systems (GNSS) have continually involved in our daily life in the past decades. Among all these GNSS-based applications, there is an increasing number of GNSS-based urban transport applications, especially the critical liability ones, such as the Electronic Toll Collection (ETC) and the Intelligent Transport System (ITS). For these GNSS-based applications, not only positioning accuracy but also its reliability is required. Latter has attracted more and more attention from urban GNSS users. Yet urban environments present great challenges for common commercial GNSS receivers since the existence of local effects such as multipath and the Non-Line-of-Sight (NLOS) receptions. The main objective of this paper is to investigate the integrity performance one can expect from a lowcost common GNSS receiver. Under this framework, this paper proposes an innovation-based integrity monitoring scheme by using an Extended Kalman Filter (EKF) with the help of carrierpower-to-noise ratio (C/N0) weighting. The derivations of the Horizontal Protection Level (HPL) for the EKF innovation-based integrity monitoring is also presented in detail. The accuracy and integrity performances are evaluated with real GPS data collected in urban environments. Compared to the classic residual-based snapshot Receiver Autonomous Integrity Monitoring (RAIM), the innovation-based EKF integrity monitoring scheme presents more advantages in terms of accuracy and integrity. With the real dataset collected in urban canyon of Nantes center, the results show that the average size of horizontal position error has been reduced by 1.15 meter with the proposed approach compared to the classic weighted RAIM, the median size of HPL has been reduced by 7.5 meters and the algorithm availability is 100% instead of 98.57%.