Abstract
In the face of a complex observation environment, the solution of the reference station of the ambiguity of network real-time kinematic (RTK) will be affected. The joint solution of multiple systems makes the ambiguity dimension increase steeply, which makes it difficult to estimate all the ambiguity. In addition, when receiving satellite observation signals in the environment with many occlusions, the received satellite observation values are prone to gross errors, resulting in obvious deviations in the solution. In this paper, a new network RTK fixation algorithm for partial ambiguity among the reference stations is proposed. It first estimates the floating-point ambiguity using the robust extended Kalman filtering (EKF) technique based on mean estimation, then finds the optimal ambiguity subset by the optimized partial ambiguity solving method. Finally, fixing the floating-point solution by the least-squares ambiguity decorrelation adjustment (LAMBDA) algorithm and the joint test of ratio (R-ratio) and bootstrapping success rate index solver. The experimental results indicate that the new method can significantly improve the fixation rate of ambiguity among network RTK reference stations and thus effectively improve the reliability of positioning results.
Highlights
China’s strong support for BeiDou satellite navigation and positioning technology and the continuous demand for positioning services require that conventional real-time kinematic (RTK) technology be more optimized both in terms of the solving accuracy of the fixed ambiguity solution, and baseline application distance between the monitoring station and the reference station
The data were collected from a monitoring station in the deformation monitoring area of a mining area in Inner Mongolia for a total of 3600 calendar elements, and measured data are collected from monitoring Station 1 in the deformation monitoring area of a ship lock in Hengxian County, Guangxi for a total of 3600 calendar elements
The fixation rate is greatly improved after adopting the partial ambiguity fixation algorithm, which is 37.04% after adopting the conventional partial ambiguity resolution (PAR) algorithm and 65.01% after adopting the new algorithm compared to the full ambiguity resolution (FAR) algorithm
Summary
China’s strong support for BeiDou satellite navigation and positioning technology and the continuous demand for positioning services require that conventional real-time kinematic (RTK) technology be more optimized both in terms of the solving accuracy of the fixed ambiguity solution, and baseline application distance between the monitoring station and the reference station. The network RTK positioning technology based on the Continuously Operating Reference Station (CORS) system arose, compared to the conventional RTK technology, which possesses the advantages of broader applications, more accurate dynamic navigation and positioning, and more reliability. When solving the network RTK inter-reference station ambiguity fixed solution timely, the observation value of the network RTK reference station is prone to gross error as the observation environment is subject to more occlusions resulting in poor satellite signals. This makes the parameter estimation results appear clear deviated or even lead to filter divergence, further affecting the overall results of network RTK precious positioning [3]
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