Time-correlated Window Carrier-phase Aided GNSS Positioning Using Factor Graph Optimization for Urban Positioning

This paper proposes an improved global navigation satellite system (GNSS) positioning method that explores the time correlation between consecutive epochs of the code and carrier phase measurements which significantly increases the robustness against outlier measurements. Instead of relying on the time difference carrier phase (TDCP) which only considers two neighboring epochs using an extended Kalman filter (EKF) estimator, this paper proposed to employ the carrier-phase measurements inside a window, the so-called window carrier-phase (WCP), to constrain the states inside a factor graph. A left null space matrix is employed to eliminate the shared unknown ambiguity variables and therefore, correlate the associated states inside the WCP. Then the pseudorange, Doppler, and the constructed WCP measurements are integrated simultaneously using factor graph optimization (FGO) to estimate the state of the GNSS receiver. We evaluated the performance of the proposed method in two typical urban canyons in Hong Kong, achieving the mean positioning error of 1.76 meters and 2.96 meters, respectively, using the automobile-level GNSS receiver. Meanwhile, the effectiveness of the proposed method is further evaluated using a low-cost smartphone level GNSS receiver and similar improvement is also obtained, compared with several existing GNSS positioning methods.