| 基于EMD-LSTM耦合预测模型的BDS多路径误差削弱方法研究 |
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| 引用本文： | 徐小汶,陶 远.基于EMD-LSTM耦合预测模型的BDS多路径误差削弱方法研究[J].全球定位系统,2020,45(2):98-104. |
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| 作者姓名： | 徐小汶 陶 远 |
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| 作者单位： | 安徽理工大学 测绘学院,安徽 淮南 232001 |
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| 基金项目： | 国家自然科学基金(1704008);安徽理工大学研究生创新基金(2019CX2077)。 |
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| 摘 要： | 北斗卫星导航系统(BDS)在短基线测量中存在的多路径误差是影响定位精度的主要误差项.针对多路径误差的非线性以及坐标序列的非平稳特性,拟采用经验模态分解(EMD)与长短期记忆网络(LSTM)结合的方法,构建EMD-LSTM耦合预测模型,对多路径误差进行预测,削弱多路径误差的影响.实验结果表明,EMD-LSTM耦合预测模型能够有效地削弱了多路径误差影响,E、N、U方向精度分别提高了22%、36%、40%.
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| 关 键 词： | 北斗导航卫星系统 多路径误差 经验模态分解 长短期记忆网络 |
BDS multipath errors reducing method based on EMD-LSTM coupled prediction model |
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| XU Xiaowen,TAO Yuan.BDS multipath errors reducing method based on EMD-LSTM coupled prediction model[J].Gnss World of China,2020,45(2):98-104. |
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| Authors: | XU Xiaowen TAO Yuan |
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| Affiliation: | (School of Geomatics,Anhui University of Science and Technology,Huainan 232001,China) |
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| Abstract: | The multipath errors in short baseline measurement of BeiDou Navigation Satellite System (BDS) were the main errors affecting positioning accuracy. Aiming at the nonlinearity of multipath errors and the non-stationarity of coordinate series, a coupled prediction model of EMD-LSTM was proposed by combining empirical mode decomposition (EMD) with long short-term memory (LSTM) to predict multipath errors and weaken the influence of multipath errors. The experimental results show that the EMD-LSTM coupled prediction model can effectively reduce the multipath errors, and the E, N,and U directions were respectively improved by 22％, 36％, and 40％. |
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| Keywords: | BeiDou navigation satellite system multipath errors empirical mode decomposition long short-term memory |
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