Abstract
In the process of BDS navigation and positioning, fast and precise ambiguity resolution plays a key role in improving the efficiency and precision of positioning. In cases of highly correlated ambiguities, since the searching space is too large, it takes a long time to fix the ambiguities. Therefore, it is very necessary to deccorelate the covariance matrix. In essence, the decorrelation process is the closest vector problem in Lattice Theory. On the basis of proving the equality of lattice reduction and decorrelation, the LLL decorrelation algorithm is analyzed and it is improved on the basis of QR decomposition. BDS triple-frequency data is adopted to carry the experiment. The decorrelation effect of the LLL and the improved LLL algorithm are analyzed from aspects of spectral condition number, average correlation coefficient and reduction time. It is proved that the improved LLL algorithm has better decorrelation effect although it requires longer reduction time.
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Xie, K., Chai, H., Pan, Z., Wang, H., Dong, B., Ming, L. (2014). Application of Improved LLL Lattice Reduction in BDS Ambiguity Decorrelation. In: Sun, J., Jiao, W., Wu, H., Lu, M. (eds) China Satellite Navigation Conference (CSNC) 2014 Proceedings: Volume III. Lecture Notes in Electrical Engineering, vol 305. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54740-9_13
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DOI: https://doi.org/10.1007/978-3-642-54740-9_13
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