Decorrelation Algorithms and Its Evaluation Indexes for GNSS Ambiguity Solution

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.