Abstract:The decorrelation algorithm can reduce the correlation of the variance-covariance of the ambiguity, decrease the candidate numbers effectively, and further increase the effect of the search. The assessment measures contain condition numbers, decorrelation coefficients and candidate numbers. However, the condition number and decorrelation coefficient can only assess the performance of decorrelation and the candidate number merely assesses search efficiency. None of these can assess the decorrelation algorithm comprehensively. Hence, in this contribution, we adopt time efficiency to assess the decorrelation algorithms. Time efficiency includes decorrelation time efficiency and search time efficiency. Simulation and real GNSS data are used to compare and analyze the three decorrelation algorithms by time efficiency measure. In terms of time efficiency, the results of the experiment show that the integer Gauss algorithm performs best, the pair Cholesky performs slightly worse than Gauss, and LLL-IGS performs worst.
SU Mingkun,ZHENG Jiansheng,YANG Yanxi et al. Time Efficiency Comparison and Analysis of Three GNSS Ambiguity Decorrelation Algorithms[J]. jgg, 2017, 37(11): 1183-1186.