一种矩阵排序改进的模糊度解算方法

A method of ambiguity resolution based on matrix ordering

针对目前应用最为广泛的最小二乘降相关平差(LAMBDA)算法涉及大量矩阵运算,延长了降相关时间的问题,提出一种矩阵排序法(MOM),来提高降相关效率。仿真实验和实测结果表明:在保持与LAMBDA算法精度相当的情况下,MOM方法可将平均解算时间从43690μs降低到40970μs。

In view of the fact that the Least-square Ambiguity Decorrelation Adjustment(LAMBDA)algorithm,which should be the most widely used method to determine the ambiguity,involves a lot of matrix operations in its decorrelation processing and prolongs the decorrelation time,this paper proposes a Matrix Ordering Method(MOM),which can improve the efficiency of decorrelation.Compared with the LAMBDA algorithm,simulation experiments and actual measurement results show that the average solution time of MOM algorithm is reduced from 43690μs to 40970μs while the accuracy of LAMBDA algorithm remains unchanged.