A partial ambiguity resolution for multi-frequency and multi-system
In response to the positioning mode of GNSS multi-frequency and multi-system,which leads to a sharp increase in the dimensionality of the overall ambiguity,making it difficult to quickly and accurately fix all ambiguities,resulting in significant RTK positioning deviations,this paper proposes a GPS/BDS/Galileo combined partial ambiguity fixing method based on Kalman filtering. Firstly,the original error equation is parameter restructured to combine narrow-lane ambiguities to form wide-lane and extra-wide-lane ambiguities,Then,multiple-constraint tests are used to round the extra-wide-lane and wide-lane ambiguities,and the estimated parameters are updated sequentially. Next,a partial ambiguity fixing strategy is applied to select a subset of narrow-lane ambiguities,reducing the search space for ambiguities. In addition,combined with inter-epoch differences,the current epoch prior position solution is provided to validate the ambiguities. Through experiments,it has been shown that in long-distance static experiments,the algorithm improves positioning accuracy by 32％,42％,and 28％in the East(E),North(N),and Up(U)directions compared to conventional ambiguity fixing methods,respectively. There is also a significant improvement in the fixed accuracy and convergence speed of ambiguity,and its advantages become more apparent with the increase of baseline length;In short distance dynamic experiments,the algorithm has shown excellent performance in positioning accuracy,reliability,and convergence speed in complex urban roads.
multi-frequency and multi-systemGNSSpartial ambiguity resolutionparameter reorganizationKalman filtertime-differenced carrier phase
万方数据
维普
