A method of improving ambiguity fixing rate for post-processing kinematic GNSS data

• Main Authors: Xiaohong Zhang, Yuxi Zhang, Feng Zhu
• Format: Article
• Language: English
• Published: SpringerOpen 2020-07-01
• Series: Satellite Navigation
• Subjects: Kinematic precise positioning; Ambiguity resolution; Ambiguity domain-based integration (ADBI); Forward–Backward Combination; Kalman filter
• Online Access: https://doi.org/10.1186/s43020-020-00022-y

Abstract Global Navigation Satellite System precise positioning using carrier phase measurements requires reliable ambiguity resolution. It is challenging to obtain continuous precise positions with a high ambiguity fixing rate under a wide range of dynamic scenes with a single base station, thus the positioning accuracy will be degraded seriously. The Forward–Backward Combination (FBC), a common post-processing smoothing method, is simply the weighted average of the positions of forward and backward filtering. When the ambiguity fixing rate of the one-way (forward or backward) filter is low, the FBC method usually cannot provide accurate and reliable positioning results. Consequently, this paper proposed a method to improve the accuracy of positions by integrating forward and backward AR, which combines the forward and backward ambiguities instead of positions—referred to as ambiguity domain-based integration (ADBI). The purpose of ADBI is to find a reliable correct integer ambiguities by making full use of the integer nature of ambiguities and integrating the ambiguities from the forward and backward filters. Once the integer ambiguities are determined correctly and reliably with ADBI, then the positions are updated with the fixing ambiguities constrained, in which more accurate positions with high confidence can be achieved. The effectiveness of the proposed approach is validated with airborne and car-borne dynamic experiments. The experimental results demonstrated that much better accuracy of position and higher ambiguity-fixed success rate can be achieved than the traditional post-processing method.