Abstract:We solve the problem of low efficiency and heavy workload in the selection of traditional GNSS carrier phase combination observations. On the basis of error analysis of the wavelength standard, ionospheric delay standard and observation noise standard of the BDS triple-frequency carrier phase combination observations, with long wavelength, weak ionosphere and weak observation noise standard as the clustering indexes, the fuzzy C-means clustering algorithm is used to optimize the data of the BDS triple-frequency carrier phase combination observations. Then, through the matrix transformation method and measured data, the integer ambiguity of the optimized combination is resolved, and the variance-covariance matrix of the combination ambiguity and the ambiguity difference between each epoch is analyzed, proving the feasibility and reliability of the method.
MENG Fanjun,LI Shujun,PAN Zongpeng et al. Optimization and Selection of BDS Triple-Frequency Carrier Phase Combination Observations Based on Fuzzy C-Means Algorithm[J]. jgg, 2019, 39(3): 246-251.