Characterization of BDS Multipath Effect Based on AT-Conv-LSTM Network

Multipath effects are the most challenging error sources for the Global Navigation Satellite System receiver, affecting observation quality and positioning accuracy. Due to the non-linear and time-varying nature, multipath error is difficult to process. Previous studies used a homogeneous indicator...

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發表在:Remote Sensing
Main Authors: Jie Sun, Zuping Tang, Chuang Zhou, Jiaolong Wei
格式: Article
語言:英语
出版: MDPI AG 2023-12-01
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在線閱讀:https://www.mdpi.com/2072-4292/16/1/73
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author Jie Sun
Zuping Tang
Chuang Zhou
Jiaolong Wei
author_facet Jie Sun
Zuping Tang
Chuang Zhou
Jiaolong Wei
author_sort Jie Sun
collection DOAJ
container_title Remote Sensing
description Multipath effects are the most challenging error sources for the Global Navigation Satellite System receiver, affecting observation quality and positioning accuracy. Due to the non-linear and time-varying nature, multipath error is difficult to process. Previous studies used a homogeneous indicator to characterize multipath effects and only revealed the temporal or spatial correlations of the multipath, resulting in limited correction performance. In this study, we consider the code multipath to be influenced not only by the elevation and azimuth angle of certain stations to satellites but also to be related to satellite characteristics such as nadir angle. Hence, azimuth angle, elevation angle, nadir angle and carrier-to-noise power density ratio are taken as multiple indicators to characterize the multipath significantly. Then, we propose an Attention-based Convolutional Long Short-Term Memory (AT-Conv-LSTM) that fully exploits the spatiotemporal correlations of multipath derived from multiple indicators. The main processing procedures using AT-Conv-LSTM are given. Finally, the AT-Conv-LSTM is applied to a station for 16 consecutive days to verify the multipath mitigation effectiveness. Compared with sidereal filtering, multipath hemispherical map (MHM) and trend-surface analysis-based MHM, the experimental results show that using AT-Conv-LSTM can decrease the root mean square error and mean absolute error values of the multipath error more than 60% and 13%, respectively. The proposed method can correct the code multipath to centimeter level, which is one order of magnitude lower than the uncorrected code multipath. Therefore, the proposed AT-Conv-LSTM network could be used as a powerful alternative tool to realize multipath reduction and will be of wide practical value in the fields of standard and high-precision positioning services.
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spelling doaj-art-5a91bdf1dfd14bacb34de536770a68612025-08-19T21:49:14ZengMDPI AGRemote Sensing2072-42922023-12-011617310.3390/rs16010073Characterization of BDS Multipath Effect Based on AT-Conv-LSTM NetworkJie Sun0Zuping Tang1Chuang Zhou2Jiaolong Wei3School of Electronic Information and Communication, Huazhong University of Science and Technology, Wuhan 430074, ChinaSchool of Electronic Information and Communication, Huazhong University of Science and Technology, Wuhan 430074, ChinaSchool of Electronic Information and Communication, Huazhong University of Science and Technology, Wuhan 430074, ChinaSchool of Electronic Information and Communication, Huazhong University of Science and Technology, Wuhan 430074, ChinaMultipath effects are the most challenging error sources for the Global Navigation Satellite System receiver, affecting observation quality and positioning accuracy. Due to the non-linear and time-varying nature, multipath error is difficult to process. Previous studies used a homogeneous indicator to characterize multipath effects and only revealed the temporal or spatial correlations of the multipath, resulting in limited correction performance. In this study, we consider the code multipath to be influenced not only by the elevation and azimuth angle of certain stations to satellites but also to be related to satellite characteristics such as nadir angle. Hence, azimuth angle, elevation angle, nadir angle and carrier-to-noise power density ratio are taken as multiple indicators to characterize the multipath significantly. Then, we propose an Attention-based Convolutional Long Short-Term Memory (AT-Conv-LSTM) that fully exploits the spatiotemporal correlations of multipath derived from multiple indicators. The main processing procedures using AT-Conv-LSTM are given. Finally, the AT-Conv-LSTM is applied to a station for 16 consecutive days to verify the multipath mitigation effectiveness. Compared with sidereal filtering, multipath hemispherical map (MHM) and trend-surface analysis-based MHM, the experimental results show that using AT-Conv-LSTM can decrease the root mean square error and mean absolute error values of the multipath error more than 60% and 13%, respectively. The proposed method can correct the code multipath to centimeter level, which is one order of magnitude lower than the uncorrected code multipath. Therefore, the proposed AT-Conv-LSTM network could be used as a powerful alternative tool to realize multipath reduction and will be of wide practical value in the fields of standard and high-precision positioning services.https://www.mdpi.com/2072-4292/16/1/73BDSmultipathAT-Conv-LSTMspatiotemporal domain
spellingShingle Jie Sun
Zuping Tang
Chuang Zhou
Jiaolong Wei
Characterization of BDS Multipath Effect Based on AT-Conv-LSTM Network
BDS
multipath
AT-Conv-LSTM
spatiotemporal domain
title Characterization of BDS Multipath Effect Based on AT-Conv-LSTM Network
title_full Characterization of BDS Multipath Effect Based on AT-Conv-LSTM Network
title_fullStr Characterization of BDS Multipath Effect Based on AT-Conv-LSTM Network
title_full_unstemmed Characterization of BDS Multipath Effect Based on AT-Conv-LSTM Network
title_short Characterization of BDS Multipath Effect Based on AT-Conv-LSTM Network
title_sort characterization of bds multipath effect based on at conv lstm network
topic BDS
multipath
AT-Conv-LSTM
spatiotemporal domain
url https://www.mdpi.com/2072-4292/16/1/73
work_keys_str_mv AT jiesun characterizationofbdsmultipatheffectbasedonatconvlstmnetwork
AT zupingtang characterizationofbdsmultipatheffectbasedonatconvlstmnetwork
AT chuangzhou characterizationofbdsmultipatheffectbasedonatconvlstmnetwork
AT jiaolongwei characterizationofbdsmultipatheffectbasedonatconvlstmnetwork