Abstract
LLL reduction algorithm has been used as a new technique of decorrelation to GNSS ambiguity resolution for recent years. The basic idea of this method is to make the variance-covariance matrix as orthogonal as possible by virtue of integer Gram-Schmidt orthogonalization, based on this we also refer to as LLL-IGS. Although LLL-IGS can indeed be used for decorrelation, the experiments indicated that it performs worse and deteriorates in some cases, especially for real GNSS data. In this contribution, (i) A modified LLL-MIGS decorrelation algorithm is proposed by improving the sorting method and removing the error of orthogonalization. (ii) The time efficiency is introduced as a new assessment criterion to measure the performance of the decorrelation algorithm directly. The time efficiency includes the decorrelation time efficiency and searching time efficiency. (iii) Real GNSS observations which including short baseline, network-based medium and long baselines have been used to compare the LLL-MIGS with LLL-IGS and also to analyze them in depth. The results of the experiments show that the LLL-MIGS method performs better than LLL-IGS method in decreasing condition number and reducing time consumption which includes the decorrelation time consumption and searching time consumption. Moreover, both of them indicate that the modified LLL-MIGS algorithm is more stable than the traditional LLL-IGS method.
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Su, M., Zheng, J., Yang, Y., Wu, Q. (2018). A Modified LLL-MIGS Decorrelation Algorithm and Time Efficiency Assessment Measure. In: Sun, J., Yang, C., Guo, S. (eds) China Satellite Navigation Conference (CSNC) 2018 Proceedings. CSNC 2018. Lecture Notes in Electrical Engineering, vol 498. Springer, Singapore. https://doi.org/10.1007/978-981-13-0014-1_43
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DOI: https://doi.org/10.1007/978-981-13-0014-1_43
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