Abstract:Least-square ambiguity decorrelation adjustment(LAMBDA) algorithm involves a lot of matrix operations and takes a long time to reduce correlation in GNSS ambiguity resolution. So, we propose a blocking in least-square ambiguity decorrelation adjustment(BLAMBDA) algorithm for conditional variance matrix partitioning. In this algorithm, the conditional variance matrix is divided into blocks to reduce the ranking times of conditional variance, and on this basis, the Cholesky decomposition formula is integrated to reduce the number multiplication operation in the process of Cholesky decomposition. Simulation experiments and measured results show that, compared with LAMBDA algorithm, the overall efficiency of BLAMBDA algorithm improves significantly, and the BLAMBDA algorithm is more stable.