Quality control for multi-GNSS uncombined PPP ambiguity resolution using a sequential Kalman filter

To achieve highest precision in positioning and navigation, frequency transfer, ionosphere monitoring, etc. with global navigation satellite system (GNSS) data, the technique of uncombined precise point positioning (PPP) ambiguity resolution holds great potential. Unified data processing and reliable ambiguity resolution for multi-GNSS are essential prerequisites. Consequently, we propose a refined approach for quality control of multi-GNSS uncombined PPP ambiguity resolution employing a sequential Kalman filter. In addition to addressing the implementation of uncombined PPP ambiguity resolution, our focus extends to the selection of the reliable ambiguity datum, computational efficiency and refining the ambiguity resolution strategy. When quad-constellation GNSS data are processed, the results demonstrate that employing the sequential Kalman filter with OpenMP can enhance computational efficiency by approximately three times compared to the standard filter. Additionally, the sequential Kalman filter is also convenient to incorporate the ambiguity datum or the fixed ambiguity as a strong constraint and complete the post-residuals check for further validating the ambiguity resolution. Following the consideration of a set of indicators, e.g., arc length, cutoff angle, ratio value and success rate, for controlling reliable ambiguity resolution, the incorrect ambiguity fixing rate can be effectively reduced, especially during the convergence stage.