An Ambiguity-free Smoothing Algorithm for Multipath Mitigation in INS/RTK Tightly-Coupled Integration

Abstract

In order to obtain high-precision positioning results in GNSS-challenged environments, Real-time kinematic (RTK) techniques are widely applied because they use double-differenced carrier phase observations to provide accurate ranging information. Traditional RTK techniques always need to resolve the integer number of carrier cycles, which is usually called “integer ambiguity”. The success rate of ambiguity resolution depends on the number of available satellites and the quality of pseudorange measurements. In GNSS-challenged environments, blockage and reflection of obstacles lead to a reduction in the number of available satellites and large multipath noise of pseudorange measurements, so the high-precision nature of RTK techniques cannot be guaranteed. On this account, this paper proposes an ambiguity-free smoothing algorithm for multipath mitigation, which eliminates invariant ambiguities within a sliding window of time. Thus, carrier phase observations are decoupled from the unknown number of relative integer ambiguities and can be directly used in the smoothing algorithm as a correction constraint for the INS kinematic model. This reduces the time spent on ambiguity searching and further speeds up the positioning process by reducing the dimension of the state variable. In order to obtain as many ambiguity-free observations as possible, our algorithm usesThus, our new algorithm uses pre-integrated the idea of pre-integration and specify the selection strategy of reference satellites. After the carrier-phase measurements are pre-processed, the remaining valid constraints will be used to detect and eliminate pseudorange outliers. The results of simulation experiments show that the algorithm of this paper can provide decimeter-level or even centimeter-level accuracy under the condition of large pseudorange multipath.