Pub Date : 2023-06-06DOI: 10.1109/ICL-GNSS57829.2023.10148924
David Märzinger, B. Etzlinger, P. Peterseil, A. Springer
A joint angle-of-arrival (AoA) and ranging estimation scheme for ultra-wideband devices is presented and experimentally evaluated. Instead of using N parallel receive chains, antenna elements are sequentially switched to the receiver, i.e., time-multiplexed. To obtain time-multiplexed measurements, a special messaging scheme is proposed that extends the conventional double-sided two-way-ranging scheme by a number of response packets that is equivalent to the number of antenna elements. Thereby, each response packet—switched through a different receive antenna—is used to record the complex-valued channel impulse response, which contains the phase information later utilized for AoA estimation. Ranging is jointly obtained through recorded receive and transmit timestamps. As the time-multiplexing introduces significant delays between phase measurements, even small synchronization errors would cause significant AoA errors. Hence, the critical building block is the clock drift compensation. The experimental evaluation with a DW1000 UWB chip and four switched λ/2 spaced antennas shows an angular accuracy of 5.5° RMSE and the capability of accurate 2-D localization.
{"title":"Time-multiplexed AoA Estimation and Ranging","authors":"David Märzinger, B. Etzlinger, P. Peterseil, A. Springer","doi":"10.1109/ICL-GNSS57829.2023.10148924","DOIUrl":"https://doi.org/10.1109/ICL-GNSS57829.2023.10148924","url":null,"abstract":"A joint angle-of-arrival (AoA) and ranging estimation scheme for ultra-wideband devices is presented and experimentally evaluated. Instead of using N parallel receive chains, antenna elements are sequentially switched to the receiver, i.e., time-multiplexed. To obtain time-multiplexed measurements, a special messaging scheme is proposed that extends the conventional double-sided two-way-ranging scheme by a number of response packets that is equivalent to the number of antenna elements. Thereby, each response packet—switched through a different receive antenna—is used to record the complex-valued channel impulse response, which contains the phase information later utilized for AoA estimation. Ranging is jointly obtained through recorded receive and transmit timestamps. As the time-multiplexing introduces significant delays between phase measurements, even small synchronization errors would cause significant AoA errors. Hence, the critical building block is the clock drift compensation. The experimental evaluation with a DW1000 UWB chip and four switched λ/2 spaced antennas shows an angular accuracy of 5.5° RMSE and the capability of accurate 2-D localization.","PeriodicalId":414612,"journal":{"name":"2023 International Conference on Localization and GNSS (ICL-GNSS)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124956627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-06DOI: 10.1109/ICL-GNSS57829.2023.10148920
M. Saajasto, M. Mäkelä, F. Prol, M. Z. H. Bhuiyan, S. Kaasalainen
With our increasing reliance on GNSS-based services for Position, Navigation, and Time (PNT), the end users require higher level corrections, for example on ionospheric delay, for more accurate positioning and navigation applications. The accuracy of the PNT services can be improved by applying correction parameters, or by utilising post-processing. In this paper we introduce a convolutional neural network based solution for estimating the ionospheric delay directly from the GNSS observables measured by the Finnish national reference station network FinnRef. Our model is able to reproduce the general shape of the ionosphere, compared against a global ionospheric map, but the model is overestimating the ionospheric delay derived from the global map. A machine learning model is computationally too heavy to be run at receiver level, however, the ionospheric delay estimates could be broadcast by the monitoring station network to increase situational awareness or as correction parameters for more precise positioning services.
{"title":"Convolutional neural network based approach for estimating ionospheric delay from GNSS observables","authors":"M. Saajasto, M. Mäkelä, F. Prol, M. Z. H. Bhuiyan, S. Kaasalainen","doi":"10.1109/ICL-GNSS57829.2023.10148920","DOIUrl":"https://doi.org/10.1109/ICL-GNSS57829.2023.10148920","url":null,"abstract":"With our increasing reliance on GNSS-based services for Position, Navigation, and Time (PNT), the end users require higher level corrections, for example on ionospheric delay, for more accurate positioning and navigation applications. The accuracy of the PNT services can be improved by applying correction parameters, or by utilising post-processing. In this paper we introduce a convolutional neural network based solution for estimating the ionospheric delay directly from the GNSS observables measured by the Finnish national reference station network FinnRef. Our model is able to reproduce the general shape of the ionosphere, compared against a global ionospheric map, but the model is overestimating the ionospheric delay derived from the global map. A machine learning model is computationally too heavy to be run at receiver level, however, the ionospheric delay estimates could be broadcast by the monitoring station network to increase situational awareness or as correction parameters for more precise positioning services.","PeriodicalId":414612,"journal":{"name":"2023 International Conference on Localization and GNSS (ICL-GNSS)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127022609","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-06DOI: 10.1109/ICL-GNSS57829.2023.10148922
Ibrahim Sbeity, C. Villien, B. Denis, E. Belmega
In the Global Navigation Satellite System (GNSS) context, the growing number of available satellites has lead to many challenges when it comes to choosing the most accurate pseudorange contributions, given the strong impact of biased measurements on positioning accuracy, particularly in single-epoch scenarios. This work leverages the potential of machine learning in predicting link-wise measurement quality factors and, hence, optimize measurement weighting. For this purpose, we use a customized matrix composed of heterogeneous features such as conditional pseudorange residuals and per-link satellite metrics (e.g., carrier-to-noise power density ratio and its empirical statistics, satellite elevation, carrier phase lock time). This matrix is then fed as an input to a recurrent neural network (RNN) (i.e., a long-short term memory (LSTM) network). Our experimental results on real data, obtained from extensive field measurements, demonstrate the high potential of our proposed solution being able to outperform traditional measurements weighting and selection strategies from state-of-the-art.
{"title":"RNN-Based GNSS Positioning using Satellite Measurement Features and Pseudorange Residuals","authors":"Ibrahim Sbeity, C. Villien, B. Denis, E. Belmega","doi":"10.1109/ICL-GNSS57829.2023.10148922","DOIUrl":"https://doi.org/10.1109/ICL-GNSS57829.2023.10148922","url":null,"abstract":"In the Global Navigation Satellite System (GNSS) context, the growing number of available satellites has lead to many challenges when it comes to choosing the most accurate pseudorange contributions, given the strong impact of biased measurements on positioning accuracy, particularly in single-epoch scenarios. This work leverages the potential of machine learning in predicting link-wise measurement quality factors and, hence, optimize measurement weighting. For this purpose, we use a customized matrix composed of heterogeneous features such as conditional pseudorange residuals and per-link satellite metrics (e.g., carrier-to-noise power density ratio and its empirical statistics, satellite elevation, carrier phase lock time). This matrix is then fed as an input to a recurrent neural network (RNN) (i.e., a long-short term memory (LSTM) network). Our experimental results on real data, obtained from extensive field measurements, demonstrate the high potential of our proposed solution being able to outperform traditional measurements weighting and selection strategies from state-of-the-art.","PeriodicalId":414612,"journal":{"name":"2023 International Conference on Localization and GNSS (ICL-GNSS)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115222711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-06DOI: 10.1109/ICL-GNSS57829.2023.10148918
Guillem Foreman-Campins, Lucía Pallarés-Rodríguez, Sergi Locubiche-Serra, G. Seco-Granados, J. López-Salcedo
This paper proposes a methodologic approach for the performance assessment of beamforming techniques for interference mitigation on GNSS receivers. While the use of spatial diversity has been studied extensively for antenna arrays with a high number of elements, few studies consider the case of a small antenna array that could fit into a handheld device. Some uncertainties arise from this problem, such as the optimal position of the antennas given the low space available, the strong dependance of the performance to the Direction-of-Arrival (DoA) of both the desired signal and the interference/s, the minimisation of complexity due to the power constraints in handheld devices and the optimal beamforming technique to apply in such a device. These problems are tackled in this paper, providing insight on the performance that can be expected. Specifically, this paper focuses on the performance for GNSS receivers. A complete analysis on the key performance indicators for GNSS is performed, focusing on the effective C/N0 and phase and code jitters that can be expected after beamforming, which give a better assessment than simply taking into account indicators such as the interference null depth.
{"title":"Methodologic Assessment of Beamforming Techniques for Interference Mitigation on GNSS Handheld Devices","authors":"Guillem Foreman-Campins, Lucía Pallarés-Rodríguez, Sergi Locubiche-Serra, G. Seco-Granados, J. López-Salcedo","doi":"10.1109/ICL-GNSS57829.2023.10148918","DOIUrl":"https://doi.org/10.1109/ICL-GNSS57829.2023.10148918","url":null,"abstract":"This paper proposes a methodologic approach for the performance assessment of beamforming techniques for interference mitigation on GNSS receivers. While the use of spatial diversity has been studied extensively for antenna arrays with a high number of elements, few studies consider the case of a small antenna array that could fit into a handheld device. Some uncertainties arise from this problem, such as the optimal position of the antennas given the low space available, the strong dependance of the performance to the Direction-of-Arrival (DoA) of both the desired signal and the interference/s, the minimisation of complexity due to the power constraints in handheld devices and the optimal beamforming technique to apply in such a device. These problems are tackled in this paper, providing insight on the performance that can be expected. Specifically, this paper focuses on the performance for GNSS receivers. A complete analysis on the key performance indicators for GNSS is performed, focusing on the effective C/N0 and phase and code jitters that can be expected after beamforming, which give a better assessment than simply taking into account indicators such as the interference null depth.","PeriodicalId":414612,"journal":{"name":"2023 International Conference on Localization and GNSS (ICL-GNSS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131864767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-06DOI: 10.1109/ICL-GNSS57829.2023.10148914
Shuo Li, M. Mikhaylov, N. Mikhaylov, T. Pany
This paper provides further details of the deep learning (DL) based integration algorithm for global navigation satellite system (GNSS) and inertial navigation system (INS) integration, where a deep neural network (DNN) is inserted into the flow of an error-state extended Kalman filter (ES-EKF) to learn the complex dynamics of the system. The proposed algorithm learns the optimal Kalman gain along with the errors in the inertial measurement units (IMU) and demonstrates superior performance over ES-EKF in terms of estimated navigation solutions and IMU errors. In this work, we analyze different implementations of the neural networks, the network architectures, and the impact of the various features to the performance of the proposed algorithm. We suggest a convolutional neural network (CNN) to extract spatial information and a long shortterm memory neural network (LSTM) to capture temporal dependencies. We justify the use of LSTM as compared to other types of recurrent neural networks (RNN). Optimal sizes for the fully connected layers, number of layers, and hidden state sizes are determined too. We report the observed difficulties in the learning, namely vanishing and exploding gradients and list the techniques we used to cope with these issues. The computational efficiency of the DL-based ES-EKF is compared to regular ES-EKF, the DL-based algorithm is supposed to fit into real-time requirements. Analysis of the impact different features have on the convergence and performance of the algorithms is carried out.
{"title":"Deep Learning Based Kalman Filter for GNSS/INS Integration: Neural Network Architecture and Feature Selection","authors":"Shuo Li, M. Mikhaylov, N. Mikhaylov, T. Pany","doi":"10.1109/ICL-GNSS57829.2023.10148914","DOIUrl":"https://doi.org/10.1109/ICL-GNSS57829.2023.10148914","url":null,"abstract":"This paper provides further details of the deep learning (DL) based integration algorithm for global navigation satellite system (GNSS) and inertial navigation system (INS) integration, where a deep neural network (DNN) is inserted into the flow of an error-state extended Kalman filter (ES-EKF) to learn the complex dynamics of the system. The proposed algorithm learns the optimal Kalman gain along with the errors in the inertial measurement units (IMU) and demonstrates superior performance over ES-EKF in terms of estimated navigation solutions and IMU errors. In this work, we analyze different implementations of the neural networks, the network architectures, and the impact of the various features to the performance of the proposed algorithm. We suggest a convolutional neural network (CNN) to extract spatial information and a long shortterm memory neural network (LSTM) to capture temporal dependencies. We justify the use of LSTM as compared to other types of recurrent neural networks (RNN). Optimal sizes for the fully connected layers, number of layers, and hidden state sizes are determined too. We report the observed difficulties in the learning, namely vanishing and exploding gradients and list the techniques we used to cope with these issues. The computational efficiency of the DL-based ES-EKF is compared to regular ES-EKF, the DL-based algorithm is supposed to fit into real-time requirements. Analysis of the impact different features have on the convergence and performance of the algorithms is carried out.","PeriodicalId":414612,"journal":{"name":"2023 International Conference on Localization and GNSS (ICL-GNSS)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121464954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-06DOI: 10.1109/ICL-GNSS57829.2023.10148915
Husnain Shahid, Luca Canzian, C. Sarto, O. Pozzobon, Joaquín Reyes-Gonzalez, G. Seco-Granados, J. López-Salcedo
Spoofing detection in Global Navigation Satellite Systems (GNSS) is gradually becoming need of the hour due to significant increase in sophisticated spoofing attacks that compromise the signal integrity and security. To withstand against these attacks, Galileo is providing the Open Service Navigation Message Authentication (OSNMA) in its E1-B signal component, comprises of a cryptographic protocol that conveys unpredictable data symbols to the user to verify the content of the I/NAV message. In this context, the following paper proposes a reliable spoofer detector by employing the snapshots of received unpredictable symbols and compares them with the authentic ones. The problem is formulated as a Binary Symmetric Channel (BSC), where the feasibility is determined by the probabilities of error at the spoofer’s and the user’s sides. However, due to the presence of signal impairments, the spoofing detector faces the hypothesis inversion problem (i.e. chooses the wrong hypothesis under certain conditions). The primary focus of this article is to avoid the hypothesis inversion problem by optimizing the statistical characterization of snapshot OSNMA detector and enhance the detection performance by designing appropriate test statistics conditions. Simulation results reveal that utilizing multiple test conditions solves the problem and strengthens the detection performance to a great extent.
{"title":"Statistical Characterization of Snapshot OSNMA Spoofing Detection","authors":"Husnain Shahid, Luca Canzian, C. Sarto, O. Pozzobon, Joaquín Reyes-Gonzalez, G. Seco-Granados, J. López-Salcedo","doi":"10.1109/ICL-GNSS57829.2023.10148915","DOIUrl":"https://doi.org/10.1109/ICL-GNSS57829.2023.10148915","url":null,"abstract":"Spoofing detection in Global Navigation Satellite Systems (GNSS) is gradually becoming need of the hour due to significant increase in sophisticated spoofing attacks that compromise the signal integrity and security. To withstand against these attacks, Galileo is providing the Open Service Navigation Message Authentication (OSNMA) in its E1-B signal component, comprises of a cryptographic protocol that conveys unpredictable data symbols to the user to verify the content of the I/NAV message. In this context, the following paper proposes a reliable spoofer detector by employing the snapshots of received unpredictable symbols and compares them with the authentic ones. The problem is formulated as a Binary Symmetric Channel (BSC), where the feasibility is determined by the probabilities of error at the spoofer’s and the user’s sides. However, due to the presence of signal impairments, the spoofing detector faces the hypothesis inversion problem (i.e. chooses the wrong hypothesis under certain conditions). The primary focus of this article is to avoid the hypothesis inversion problem by optimizing the statistical characterization of snapshot OSNMA detector and enhance the detection performance by designing appropriate test statistics conditions. Simulation results reveal that utilizing multiple test conditions solves the problem and strengthens the detection performance to a great extent.","PeriodicalId":414612,"journal":{"name":"2023 International Conference on Localization and GNSS (ICL-GNSS)","volume":"65 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130769110","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-06DOI: 10.1109/ICL-GNSS57829.2023.10148927
Lucía Pallarés-Rodríguez, G. Seco-Granados, J. López-Salcedo
This paper analyses the impact of exploiting polarization diversity for multipath mitigation in GNSS handheld receivers. While the use of array processing techniques has been widely studied in the field of multipath mitigation, few studies consider receivers equipped with very small antenna arrays, which is the case of handheld devices. When working with few antennas some performance limitations appear due to the small size of the array, so these must be counteracted by exploiting additional information available at the receiver. One possible solution is to make use of polarization diversity, taking advantage of the fact that in most multipath scenarios, reflected replicas tend to have a different polarization from that of the desired signal. Therefore, this paper evaluates the performance of some array processing techniques when combined with dual-polarized antennas, showing that the small size of the array can be effectively counteracted by exploiting polarization diversity when combating multipath.
{"title":"Dual-Polarization Beamforming Techniques for Multipath Mitigation in GNSS Handheld Receivers","authors":"Lucía Pallarés-Rodríguez, G. Seco-Granados, J. López-Salcedo","doi":"10.1109/ICL-GNSS57829.2023.10148927","DOIUrl":"https://doi.org/10.1109/ICL-GNSS57829.2023.10148927","url":null,"abstract":"This paper analyses the impact of exploiting polarization diversity for multipath mitigation in GNSS handheld receivers. While the use of array processing techniques has been widely studied in the field of multipath mitigation, few studies consider receivers equipped with very small antenna arrays, which is the case of handheld devices. When working with few antennas some performance limitations appear due to the small size of the array, so these must be counteracted by exploiting additional information available at the receiver. One possible solution is to make use of polarization diversity, taking advantage of the fact that in most multipath scenarios, reflected replicas tend to have a different polarization from that of the desired signal. Therefore, this paper evaluates the performance of some array processing techniques when combined with dual-polarized antennas, showing that the small size of the array can be effectively counteracted by exploiting polarization diversity when combating multipath.","PeriodicalId":414612,"journal":{"name":"2023 International Conference on Localization and GNSS (ICL-GNSS)","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131846877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-06DOI: 10.1109/ICL-GNSS57829.2023.10148928
Toni Hammarberg, J. V. Garcia, Jarno N. Alanko, M. Z. H. Bhuiyan
We present Galileo Open Service Navigation Message Authentication (OSNMA) observed operational information and key performance indicators (KPIs) from the analysis of a four day long dataset collected in static open sky condition in southern Finland and using our in-house developed OSNMA implementation. In particular, we present a timeline with authentication related events such as authentication status and type, dropped navigation pages and failed cyclic redundancy checks. We also report KPIs such as the number of simultaneously authenticated satellites over time, percentage of authenticated fixes and time to first authenticated fix, and study how the satellite visibility affects these figures. Finally, we analyze situations where it was not possible to reach an authenticated fix, and offer our findings on the observed patterns.
{"title":"An Experimental Performance Assessment of Galileo OSNMA","authors":"Toni Hammarberg, J. V. Garcia, Jarno N. Alanko, M. Z. H. Bhuiyan","doi":"10.1109/ICL-GNSS57829.2023.10148928","DOIUrl":"https://doi.org/10.1109/ICL-GNSS57829.2023.10148928","url":null,"abstract":"We present Galileo Open Service Navigation Message Authentication (OSNMA) observed operational information and key performance indicators (KPIs) from the analysis of a four day long dataset collected in static open sky condition in southern Finland and using our in-house developed OSNMA implementation. In particular, we present a timeline with authentication related events such as authentication status and type, dropped navigation pages and failed cyclic redundancy checks. We also report KPIs such as the number of simultaneously authenticated satellites over time, percentage of authenticated fixes and time to first authenticated fix, and study how the satellite visibility affects these figures. Finally, we analyze situations where it was not possible to reach an authenticated fix, and offer our findings on the observed patterns.","PeriodicalId":414612,"journal":{"name":"2023 International Conference on Localization and GNSS (ICL-GNSS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126067832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-06DOI: 10.1109/icl-gnss57829.2023.10148926
{"title":"ICL-GNSS 2023 Cover Page","authors":"","doi":"10.1109/icl-gnss57829.2023.10148926","DOIUrl":"https://doi.org/10.1109/icl-gnss57829.2023.10148926","url":null,"abstract":"","PeriodicalId":414612,"journal":{"name":"2023 International Conference on Localization and GNSS (ICL-GNSS)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126237962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-06DOI: 10.1109/ICL-GNSS57829.2023.10148921
Mikko Kotilainen, M. Mäkelä, K. Hanhijärvi, Martta-Kaisa Olkkonen, A. Wallin, T. Fordell, S. Kaasalainen
The aim of this paper is to reduce the noise level in the time signals of the Global Navigation Satellite Systems (GNSS). This is done by finding patterns in the Common Generic GNSS Timing Transfer Standard (CGGTTS) data, as the pseudorange residuals in this data appear to include patterns that repeat every day. The reduced noise level allows for easier detection of possible anomalies in the time signals of individual GNSS satellites and hence increases the resilience of the GNSS time measurement. The observed patterns are explainable by multipath, repeating every time the satellite is at a certain position in its groundtrack.
{"title":"Detecting consistent patterns in pseudorange residuals in GNSS timing data","authors":"Mikko Kotilainen, M. Mäkelä, K. Hanhijärvi, Martta-Kaisa Olkkonen, A. Wallin, T. Fordell, S. Kaasalainen","doi":"10.1109/ICL-GNSS57829.2023.10148921","DOIUrl":"https://doi.org/10.1109/ICL-GNSS57829.2023.10148921","url":null,"abstract":"The aim of this paper is to reduce the noise level in the time signals of the Global Navigation Satellite Systems (GNSS). This is done by finding patterns in the Common Generic GNSS Timing Transfer Standard (CGGTTS) data, as the pseudorange residuals in this data appear to include patterns that repeat every day. The reduced noise level allows for easier detection of possible anomalies in the time signals of individual GNSS satellites and hence increases the resilience of the GNSS time measurement. The observed patterns are explainable by multipath, repeating every time the satellite is at a certain position in its groundtrack.","PeriodicalId":414612,"journal":{"name":"2023 International Conference on Localization and GNSS (ICL-GNSS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122230880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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