GNSS模糊度降相关算法及其评价指标研究
Decorrelation Algorithms and Its Evaluation Indexes for GNSS Ambiguity Solution
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摘要: 针对Gauss、LDL和LLL算法构造整数阵存在的实数阵元素计算、实数至整数阵转换的排序问题,分别研究了相应的元素升序降相关算法和整逆型(先求逆后取整)降相关算法。分析了谱条件数、降相关系数和平均相关系数等降相关算法评价指标的优缺点,提出了等效相关系数评价指标。研究结果表明,等效相关系数较其他3种指标能更有效地评价不同维数方差阵,尤其是高维情况的降相关算法效果;逆整型优于整逆型降相关算法,升序(逆整型)降相关算法更佳,且优劣顺序为升序LDL、升序Gauss和升序LLL算法。Abstract: Ambiguity decorrelation is a useful technique for higher success rate and reliability of rapid ambiguity resolution.In this contribution integer Gaussian(Gauss),inverse integer Cholesky(LDL) and LLL decorrelation algorithm are studied from real number calculation order and real-to-integer transformation strategy,on which both ascending sort and integer inverse decoration algorithm are presented for enhancing the ambiguity resolution performance.An equivalence correlation coefficient is proposed by analyzing advantages and disadvantages of condition number,decorrelation coefficient and average correlation coefficient employed for decorrelation evaluation.The results show that the equivalence correlation coefficient outperforms three evaluation indexes mentioned above especially for high dimensional covariance matrix.All decorrelation algorithms is improved by ascending sort,and inverse-integer decorrelation algorithms is superior to integer-inverse ones with LDL,Gauss and LLL preferential order.