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Multipath Suppressing Method Based on Pseudorange Model Using Modified Teaching-Learning Based Optimization Algorithm

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Chinese Journal of Electronics 2022年第5期31卷 821-831页

作者： CHENG Lan ZHANG Jing NI Zihang YAN Gaowei Taiyuan University of Technology Xi'an Branch of China Telecom Co.Ltd.

Satellites based positioning has been widely applied to many areas in our daily lives and thus become indispensable, which also leads to increasing demand for high-positioning accuracy. In some complex environments(such as dense urban, valley), multipath interference is one of the main error sources deteriorating positioning accuracy, and it is difficult to eliminate via differential techniques due to its uncertainty of occurrence and irrelevance in different instants. To address this problem,we propose a positioning method for global navigation satellite systems(GNSS) by adopting a modified teachinglearning based optimization(TLBO) algorithm after the positioning problem is formulated as an optimization problem. Experiments are conducted by using actual satellite data. The results show that the proposed positioning algorithm outperforms other algorithms, such as particle swarm optimization based positioning algorithm,differential evolution based positioning algorithm, variable projection method, and TLBO algorithm, in terms of accuracy and stability.

关键词： global navigation satellite systems satellite navigation particle swarm optimisation optimization problem Global Positioning System pseudorange model optimisation modified teaching-learning based optimization algorithm high-positioning accuracy positioning method particle swarm optimization position control evolutionary computation actual satellite data satellites based positioning dense urban valley variable projection method main error sources positioning problem positioning algorithm TLBO algorithm

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