Abstract: The improved united ambiguity decorrelation is proposed by analyzing the deficiency of united ambiguity decorrelation algorithms.The improved united ambiguity decorrelation needs search the most precise ambiguity to decorrelate before every decorrelation process and the conditional variances should be distributed in descending order approximately.The performances of the united ambiguity decorrelation algorithm and the improved united ambiguity decorrelation algorithm are compared by using 6 symmetric and positive definite matrixes derived from a random simulation for high dimension and low dimension,respectively.The results show the improved united ambiguity decorrelation algorithm is able to decorrelate the correlation of variance-covariance and has better performances on decreasing the time of decorrelation process and search process.