2020 International Conference on Localization and GNSS (ICL-GNSS)最新文献_第2页

Signal performance analysis of the latest quartet of Galileo satellites during the first operational year 最新的伽利略四颗卫星在第一年运行期间的信号性能分析

2020 International Conference on Localization and GNSS (ICL-GNSS) Pub Date : 2020-06-01 DOI: 10.1109/ICL-GNSS49876.2020.9115548

C. Andrei, J. Johansson, H. Koivula, M. Poutanen

{"title":"Signal performance analysis of the latest quartet of Galileo satellites during the first operational year","authors":"C. Andrei, J. Johansson, H. Koivula, M. Poutanen","doi":"10.1109/ICL-GNSS49876.2020.9115548","DOIUrl":"https://doi.org/10.1109/ICL-GNSS49876.2020.9115548","url":null,"abstract":"On 12 February 2020, the latest four Galileo satellites had completed one full year of space operational service. The satellites were launched on 25 July 2018. The quartet increased the operational capacity of the Galileo constellation to 22 satellites. This study reports on three signal-in-space (SiS) performance indicators - status, availability, and ranging accuracy - from 11 February 2019 to 12 February 2020. In addition, the study looks also at how the on-board satellite clocks have performed. The data analysis shows 100% data validity and signal health status for three our of the four satellites, whereas NAPA (No Accuracy Prediction Available) events accounted for about 2% of the time. In addition, SiS availability was higher than 95% in the first operational year. Furthermore, the 95th percentile of the global average of the instantaneous signal in space error is found to vary between 0.17 to 0.33 m on monthly basis. Lastly, the precise satellite clock biases show high short-term performance with 0.1 ps/s (10−13 s/s) standard deviations during the first operational year. The numerical results indicate a robust performance and high reliability for the youngest Galileo satellites in the constellation. They increase the number of operational satellites in the constellation and thus contribute to the Galileo’s increased popularity in the satellite-based positioning and navigation user community.","PeriodicalId":123786,"journal":{"name":"2020 International Conference on Localization and GNSS (ICL-GNSS)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121214828","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}

引用次数: 4

Audio Source Positioning Based on Angle of Arrival Measurements Using Particle Filter 基于粒子滤波到达角测量的声源定位

2020 International Conference on Localization and GNSS (ICL-GNSS) Pub Date : 2020-06-01 DOI: 10.1109/ICL-GNSS49876.2020.9115497

Mikko Lager, S. Ali-Löytty, R. Piché

引用次数: 0

Analyzing Android GNSS Raw Measurements Flags Detection Mechanisms for Collaborative Positioning in Urban Environment 城市环境下协同定位的Android GNSS原始测量标志检测机制分析

2020 International Conference on Localization and GNSS (ICL-GNSS) Pub Date : 2020-06-01 DOI: 10.1109/ICL-GNSS49876.2020.9115564

Thomas Verheyde, Antoine Blais, C. Macabiau, F. Marmet

{"title":"Analyzing Android GNSS Raw Measurements Flags Detection Mechanisms for Collaborative Positioning in Urban Environment","authors":"Thomas Verheyde, Antoine Blais, C. Macabiau, F. Marmet","doi":"10.1109/ICL-GNSS49876.2020.9115564","DOIUrl":"https://doi.org/10.1109/ICL-GNSS49876.2020.9115564","url":null,"abstract":"The release of Android GNSS raw measurements, in late 2016, unlocked the access of smartphones’ technologies for advanced positioning applications. Recently, smartphones’ GNSS capabilities were optimized with the release of multi-constellation and multi-frequency GNSS chipsets. In the last few years, several papers studied the use of Android raw data measurements for developing advanced positioning techniques such as Precise Point Positioning (PPP) or Real-Time Kinematic (RTK), and quantified those measurements compare to high-end commercial receivers. However, characterizing different smartphone models and chipset manufacturers in urban environment remains an unaddressed challenge. In this paper, a thorough data analysis will be conducted based on a data collection campaign that took place in Toulouse city center. Collaborative scenarios have been put in place while navigating in deep urban canyons. Two vehicles were used for this experiment protocol, equipped with high-end GNSS receivers for reference purposes, while seven smartphones were tested. Android algorithms reliability of both the multipath and cycle slip flags were investigated and evaluated as potential performance parameters. Our study suggests that their processing may differ from one brand to another, making their use as truthful quality indicators for collaborative positioning yet open to debate.","PeriodicalId":123786,"journal":{"name":"2020 International Conference on Localization and GNSS (ICL-GNSS)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125878106","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}

引用次数: 6

Sub-Messages Scheduling in GNSS Packet Broadcasting By Message Splitting 基于消息拆分的GNSS分组广播子消息调度

2020 International Conference on Localization and GNSS (ICL-GNSS) Pub Date : 2020-06-01 DOI: 10.1109/ICL-GNSS49876.2020.9115495

F. Ardizzon, N. Laurenti, S. Tomasin

{"title":"Sub-Messages Scheduling in GNSS Packet Broadcasting By Message Splitting","authors":"F. Ardizzon, N. Laurenti, S. Tomasin","doi":"10.1109/ICL-GNSS49876.2020.9115495","DOIUrl":"https://doi.org/10.1109/ICL-GNSS49876.2020.9115495","url":null,"abstract":"Recently, global navigation satellite systems (GNSSs) have started offering additional services to improve the precision of positioning, authenticate the GNSS signal, and broadcast messages (e.g., almanacs or information needed for search and rescue purposes). In all these scenarios, possibly long messages must be broadcast over the low-rate satellite-ground communication link. By splitting the message into sub-messages, each transmitted by a different satellite, the receiver can decode them simultaneously, achieving a higher equivalent data rate. In this paper we address the problem of scheduling sub-message transmissions on a constellation of satellites for transmission over error-free and erasure channels. For the error-free case we aim at maximizing the area over the earth, where the entire message can be decoded. Both optimal (by binary linear programming) and sub-optimal low-complexity solutions are investigated. For erasure channels we consider two possible targets: either the minimization of the maximum packet error rate (PER) on the earth surface, or, in a dual fashion, the maximization of the area where all sub-messages are received with PER below a given threshold. Both problems are framed as integer linear programming problems, and again suboptimal, less computationally demanding solutions are also developed.","PeriodicalId":123786,"journal":{"name":"2020 International Conference on Localization and GNSS (ICL-GNSS)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127983365","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}

引用次数: 1

Positioning Based on Noise-Limited Censored Path Loss Data 基于限噪截后路径损耗数据的定位

2020 International Conference on Localization and GNSS (ICL-GNSS) Pub Date : 2020-06-01 DOI: 10.1109/ICL-GNSS49876.2020.9115572

A. Karttunen, M. Valkama, J. Talvitie

{"title":"Positioning Based on Noise-Limited Censored Path Loss Data","authors":"A. Karttunen, M. Valkama, J. Talvitie","doi":"10.1109/ICL-GNSS49876.2020.9115572","DOIUrl":"https://doi.org/10.1109/ICL-GNSS49876.2020.9115572","url":null,"abstract":"Positioning is considered one of the most important features and enabler of various novel industry verticals in future radio systems. Since path loss or received signal strength-based measurements are widely available and accessible in the majority of wireless standards, path loss-based positioning has an important role among other positioning technologies. Conventionally path loss-based positioning has two phases; i) fitting a path loss model to training data, if such training data is available, and ii) determining link distance estimates based on the path loss model and calculating the position estimate. However, in both phases, the maximum measurable path loss is limited by measurement noise. Such immeasurable samples are called censored path loss data and such noisy data is commonly neglected in both the model fitting and in the positioning phase. In the case of censored path loss, the loss is known to be above a known threshold level and that information can be used in model fitting as well as in the positioning phase. In this paper, we examine and propose how to use censored path loss data in path loss model-based positioning and demonstrate with simulations the potential of the proposed approach for considerable improvements (over 30%) in positioning accuracy.","PeriodicalId":123786,"journal":{"name":"2020 International Conference on Localization and GNSS (ICL-GNSS)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132557931","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}

引用次数: 2

Radio-based Sensing and Indoor Mapping with Millimeter-Wave 5G NR Signals 基于毫米波5G NR信号的无线传感和室内测绘

2020 International Conference on Localization and GNSS (ICL-GNSS) Pub Date : 2020-06-01 DOI: 10.1109/ICL-GNSS49876.2020.9115568

Carlos Baquero Barneto, T. Riihonen, Matias Turunen, Mike Koivisto, J. Talvitie, M. Valkama

引用次数: 18

Deep Learning Based Localization and HO Optimization in 5G NR Networks 基于深度学习的5G NR网络定位与HO优化

2020 International Conference on Localization and GNSS (ICL-GNSS) Pub Date : 2020-06-01 DOI: 10.1109/ICL-GNSS49876.2020.9115530

Roman Klus, Lucie Klus, D. Solomitckii, M. Valkama, J. Talvitie

{"title":"Deep Learning Based Localization and HO Optimization in 5G NR Networks","authors":"Roman Klus, Lucie Klus, D. Solomitckii, M. Valkama, J. Talvitie","doi":"10.1109/ICL-GNSS49876.2020.9115530","DOIUrl":"https://doi.org/10.1109/ICL-GNSS49876.2020.9115530","url":null,"abstract":"In the emerging 5G radio networks, beamforming-capable nodes are able to densely cover narrow areas with a high-quality signal. Such systems require high-level handover management system to proactively react to upcoming changes in signal quality, while restricting common issues such as ping-ponging or fast-shadowing of the signal. The utilization of deep learning in such a system allows for dynamic optimization of the system policies, based directly on the past behavior of the users and their channel responses. Our approach on handover optimization is purely non-deterministic, proving the idea that a self-learning network is able to efficiently manage user mobility in dense network scenario. The proposed network consists of feature extractors and dense layers. The model is trained in two stages, first serves as an initial weight setting in supervised fashion based on 3GPP model. The second stage is an optimization problem to reduce the number of unnecessary handovers while sustaining a high-quality connection. The model is also trained to predict the user location information as the second output. The presented results show that the number of handovers can be significantly reduced without decreasing the throughput of the system. The predicted location of the user has meter-level accuracy.","PeriodicalId":123786,"journal":{"name":"2020 International Conference on Localization and GNSS (ICL-GNSS)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128415804","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}

引用次数: 8

New Cluster Selection and Fine-grained Search for k-Means Clustering and Wi-Fi Fingerprinting 基于k均值聚类和Wi-Fi指纹的新聚类选择和细粒度搜索

2020 International Conference on Localization and GNSS (ICL-GNSS) Pub Date : 2020-06-01 DOI: 10.1109/ICL-GNSS49876.2020.9115419

J. Torres-Sospedra, Darwin Quezada-Gaibor, G. M. Mendoza-Silva, J. Nurmi, Y. Koucheryavy, J. Huerta

引用次数: 14

Opportunities and challenges of Galileo E5 wideband real signals processing 伽利略E5宽带真实信号处理的机遇与挑战

2020 International Conference on Localization and GNSS (ICL-GNSS) Pub Date : 2020-06-01 DOI: 10.1109/ICL-GNSS49876.2020.9115573

N. Linty, M. Z. H. Bhuiyan, M. Kirkko-Jaakkola

引用次数: 2

NLOS Detection using UWB Channel Impulse Responses and Convolutional Neural Networks 基于超宽带信道脉冲响应和卷积神经网络的非视点检测

2020 International Conference on Localization and GNSS (ICL-GNSS) Pub Date : 2020-06-01 DOI: 10.1109/ICL-GNSS49876.2020.9115498

Maximilian Stahlke, Sebastian Kram, Christopher Mutschler, T. Mahr

引用次数: 37