模糊度降相关的整数分块正交化算法

随着模糊度实数解协方差矩阵维数的增加，由于取整运算舍入误差的影响，LLL降相关算法的成功率低、降相关效果差。本文引入分块正交的思想，设计了整数分块Gram-Schmidt正交化算法，同时联合LLL算法提出了基于整数分块正交化的LLL降相关算法（IBGS-LLL）。利用随机模拟的方法，分析了不同维数下不同分块方式的降相关效果，明确了不同模式下算法的分块方式。在动态和静态模式下与改进的LLL算法进行了比较，证明了IBGS-LLL算法在模糊度协方差矩阵降相关方面具有更优的效果和更高的成功率。

Ambiguity Decorrelation with Integer Block Orthogonal ization Algorithm

Since the round-off error will affect the effect and the success rate of the down correlation along with the increase of the matrix’s dimension，this paper introduces the idea of block Gram-Schmidt orthogonalization, and designs the Integer Block Gram-Schmidt Orthogonalization algorithm, meanwhile combines the LLL algorithm to propose the IBGS-LLL decorrelation algorithm. It analyzes the decorrelation effect of different block style with different dimension by using the random simulation method, and confirms the block manner of different measuring mode. This paper compares the IBGS-LLL algorithm with the improved LLL algorithm under kinematic and static mode to prove that the IBGS-LLL decorrelation algorithm possessing has better effect and higher success rate of ambiguity decorrelation.