Abstract
The carrier-based kinematic-to-kinematic relative positioning can obtain the precise baseline between two moving stations, which greatly expands the application field of dynamic relative positioning. However, the relative positioning performance is degraded greatly with low fixation rate of ambiguity with low-cost receivers. Especially, in the complex dynamic environment, ambiguity resolution effect is influenced by the satellite signal blocked, multipath outlier, and abnormal state prediction. Aiming at the problems, a novel inertial navigation system–aided robust adaptive filtering ambiguity resolution model is proposed. In addition, a hierarchical filtering strategy is developed to eliminate ambiguity parameters in BeiDou navigation satellite system/inertial navigation system tightly coupled integrated system. Finally, the precise relative position can be calculated with the “best” ambiguity solution. Both experiments with static data and field vehicle test were carried out to evaluate the algorithm efficiency in different data configurations. The results indicate that IRAFAR-TCRP method can effectively suppress the influence of observation outliers and model prediction abnormalities, which improves the success rate of ambiguity resolution, raises the accuracy as well as the continuity of relative positioning. The success rate of ambiguity resolution with single-frequency BeiDou navigation satellite system can reach 90% in the gross error and abnormal disturbance environments and centimeter-level accuracy can be achieved.
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More From: International Journal of Distributed Sensor Networks
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