引用本文: 谢恺, 柴洪洲, 范龙, 潘宗鹏. 一种改进的LLL模糊度降相关算法[J]. 武汉大学学报 ( 信息科学版), 2014, 39(11): 1363-1368.
Xie Kai, Chai Hongzhou, Fan Long, Pan Zongpeng. An Improved LLL Ambiguity Decorrelation Algorithm[J]. Geomatics and Information Science of Wuhan University, 2014, 39(11): 1363-1368.
 Citation: Xie Kai, Chai Hongzhou, Fan Long, Pan Zongpeng. An Improved LLL Ambiguity Decorrelation Algorithm[J]. Geomatics and Information Science of Wuhan University, 2014, 39(11): 1363-1368.

## An Improved LLL Ambiguity Decorrelation Algorithm

• 摘要: 针对GNSS载波相位精密定位中的整周模糊度解算问题，引入格基规约的思想，基于系统旋转的Houscholder正交变换对现有的LLL规约算法进行了改进，并将长度规约的比较范围扩大到n维，对规约基向量进行预排序，提出了HE-LLL规约算法。在不同观测时段长度和不同基线长度的情况下，分别从条件数、规约时间、非正交化指标以及正交化列向量长度变化趋势等方面将HE-LLL规约算法与改进前算法的规约效果进行了比较，结果表明，HE-LLL算法大大提高了规约效率，且对正交化列向量的长度具有很好的约束作用。

Abstract: A new lattice reduction method is introduced to solve the problem of integer ambiguity resolution in UNSS carrier phase precise positioning. The current LLL reduction algorithm is improved based on a orthogonal Householder transformation with systematic rotation. The comparative range is extended to n. The reduction base vectors are preordered and a HE-LLL reduction algorithm is proposed. Experiments with different time intervals and baseline lengths were executed and a comparison was made between the HE-LLL algorithm and other algorithm concerning condition number，non-or-thogonalindex，reduction time，and changing trend of the length of orthogonal row vector. The recults show that the HE-LLL algorithm has improved reduction efficiency，and can well restrict the length of orthogonal row vector.

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