2017 International Conference on Localization and GNSS (ICL-GNSS)最新文献_第2页

Optimization of anchor nodes' usage for location verification systems 定位验证系统锚节点使用的优化

2017 International Conference on Localization and GNSS (ICL-GNSS) Pub Date : 2017-06-27 DOI: 10.1109/ICL-GNSS.2017.8376254

G. Caparra, Marco Centenaro, N. Laurenti, S. Tomasin

引用次数: 6

Trading-off location accuracy and service quality: Privacy concerns and user profiles 权衡位置准确性和服务质量:隐私问题和用户配置文件

2017 International Conference on Localization and GNSS (ICL-GNSS) Pub Date : 2017-06-27 DOI: 10.1109/ICL-GNSS.2017.8376244

Z. Gardner, D. Leibovici, A. Bassiri, G. Foody

引用次数: 10

Algorithms for relative train localization with GNSS and track map: Evaluation and comparison 基于GNSS和轨道图的列车相对定位算法:评价与比较

2017 International Conference on Localization and GNSS (ICL-GNSS) Pub Date : 2017-06-27 DOI: 10.1109/ICL-GNSS.2017.8376253

B. Siebler, F. Müller, O. Heirich, S. Sand

{"title":"Algorithms for relative train localization with GNSS and track map: Evaluation and comparison","authors":"B. Siebler, F. Müller, O. Heirich, S. Sand","doi":"10.1109/ICL-GNSS.2017.8376253","DOIUrl":"https://doi.org/10.1109/ICL-GNSS.2017.8376253","url":null,"abstract":"Large safety distances between consecutive trains limit the flexibility and capacity of rail traffic. The introduction of automatic distance control between trains has the potential to reduce the safety distances. This requires an accurate and reliable distance estimation. In this paper, we therefore evaluate the performance of a relative localization system that tightly integrates the global satellite navigation system (GNSS) measurements and a map of the track network. The tight integration reduces the absolute train position to a 1-D value that describes the position on a track. The relative position is then calculated by subtracting two 1-D positions. In an empirical evaluation the tightly integrated system is compared to a loosely integrated system and a cooperative approach based solely on GNSS measurements. The cooperative approach uses GNSS pseudorange and range rate double differences, to determine the baseline between two antennas. For the loosely integrated system first the 3-D train position is estimated in an extended Kalman filter (EKF). In a second step, this position is matched to the map to obtain the position on the track. The relative position root-mean-square error (RMSE) of the different approaches is determined with a 167 km long data set, measured on a diesel train over the duration of 6 hours. The data set is divided into open sky, suburban and forest environments. For each of these environments, six different antenna distances are evaluated. The results show that the tightly and loosely integrated systems have a considerable smaller RMSE than the cooperative approach. The difference in the average performance of the two map based approaches is negligible. An advantage of the tight integration can be seen only under poor satellite visibility conditions that were encountered only sporadic during the measurements.","PeriodicalId":330366,"journal":{"name":"2017 International Conference on Localization and GNSS (ICL-GNSS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125764656","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

The development of occupancy monitoring for removing uncertainty within building energy management systems 开发占用监测以消除建筑能源管理系统中的不确定性

2017 International Conference on Localization and GNSS (ICL-GNSS) Pub Date : 2017-06-27 DOI: 10.1109/ICL-GNSS.2017.8376240

Sophie Naylor, M. Gillott, G. Herries

{"title":"The development of occupancy monitoring for removing uncertainty within building energy management systems","authors":"Sophie Naylor, M. Gillott, G. Herries","doi":"10.1109/ICL-GNSS.2017.8376240","DOIUrl":"https://doi.org/10.1109/ICL-GNSS.2017.8376240","url":null,"abstract":"This paper provides an overview of methods and models used for the localised detection of building occupants by combining data from a range of sensor types, and the prediction of future occupancy rates based on past data. The occupancy detection proposed here is designed to be implemented as part of a real-time responsive building energy management system, catering building energy use directly to occupant needs. The initial stages of testing used sensor data collected in a small office building in Nottingham, UK. A Neural Network model was trained using data from local environmental sensors, including CO2 level, motion detection, temperature, window status and the detection of personal mobile devices through Wi-Fi and Bluetooth connections. A predictive neural network model was also trained using simulated occupancy rates, with consideration for the level of uncertainty in the model outputs. The results of the study show that the combination of a select group of sensors can provide a lower error in the estimated number of occupants per zone than any single sensor type alone. However, when limited training data is available, it is not viable to include all sensors in the model, as this leads to overfitting. The sensors that give the greatest information gain were found to be best identified by comparing the occupancy estimation made by each sensor individually. It was found that the predictive model outperformed simpler occupancy prediction heuristics, especially when occupant behaviours differ from typical patterns.","PeriodicalId":330366,"journal":{"name":"2017 International Conference on Localization and GNSS (ICL-GNSS)","volume":"118 34","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120820575","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

Analysis of radar sensing coverage of a passive GNSS-based SAR system 基于被动gnss的SAR系统雷达感知覆盖分析

2017 International Conference on Localization and GNSS (ICL-GNSS) Pub Date : 2017-06-27 DOI: 10.1109/ICL-GNSS.2017.8376246

Yu Zheng, Yang Yang, Wu Chen

引用次数: 4

Indoor localization for Bluetooth low energy using wavelet and smoothing filter 基于小波滤波和平滑滤波的低功耗蓝牙室内定位

2017 International Conference on Localization and GNSS (ICL-GNSS) Pub Date : 2017-06-27 DOI: 10.1109/ICL-GNSS.2017.8376247

Xiaoyue Hou, T. Arslan, Jiacheng Gu

引用次数: 10

Mathematical underpinnings of crowdsource GPS jammer geolocation using signal strength readings from various locations 使用来自不同位置的信号强度读数的众包GPS干扰器地理定位的数学基础

2017 International Conference on Localization and GNSS (ICL-GNSS) Pub Date : 2017-06-01 DOI: 10.1109/ICL-GNSS.2017.8376243

Barry R. Secrest, D. Richie, B. Rapp

引用次数: 2

Additional SQM metrics for generic TM detection 用于通用TM检测的附加SQM指标

2017 International Conference on Localization and GNSS (ICL-GNSS) Pub Date : 2017-06-01 DOI: 10.1109/ICL-GNSS.2017.8376249

J. Pagot, O. Julien, Ikhlas Selmi

{"title":"Additional SQM metrics for generic TM detection","authors":"J. Pagot, O. Julien, Ikhlas Selmi","doi":"10.1109/ICL-GNSS.2017.8376249","DOIUrl":"https://doi.org/10.1109/ICL-GNSS.2017.8376249","url":null,"abstract":"The ICAO Threat Model describes three cases of distortions that can occur on GPS L1 C/A signals. It defines digital and analog failures that may occur on the satellite payload. To cover a wider area of possible distortions, a Generic Threat Model (TM) based on the Fourier Transform of the signal distortions is proposed. Then, the distortion effects have to be detected and mitigated through Signal Quality Monitoring (SQM) algorithm, which is implemented on SBAS and GBAS ground infrastructures. The basic form of SQM uses simple metrics based on correlator outputs that are normalized by the correlation function prompt. Those normalized outputs can be used directly as a simple ratio metrics. They can also be combined to compute difference or sum metrics between symmetric correlator outputs pairs (with respect to the prompt) [1]. In this paper, an extended set of metrics is tested. It includes simple ratio, sum and difference between all monitored correlator outputs. The influence of several parameters related to correlator output positions is studied. The benefits provided by these new metrics compared to a baseline SQM are assessed and conclusions on the performed SQMs are made. The carried out tests are applied to Galileo E1 OS signals.","PeriodicalId":330366,"journal":{"name":"2017 International Conference on Localization and GNSS (ICL-GNSS)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131293827","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

Asymptotic fault-tolerant fusion algorithm based on P-value mapping for multi-sensors navigation 基于p值映射的多传感器导航渐近容错融合算法

2017 International Conference on Localization and GNSS (ICL-GNSS) Pub Date : 2017-06-01 DOI: 10.1109/ICL-GNSS.2017.8376245

Rong Wang, Zhi Xiong, Jianye Liu, Rongbing Li, Yuxuan Cao

引用次数: 2

Effect of non-integer delay on ranging accuracy for ultra-reliable systems 非整数延迟对超可靠系统测距精度的影响

2017 International Conference on Localization and GNSS (ICL-GNSS) Pub Date : 2017-06-01 DOI: 10.1109/ICL-GNSS.2017.8376239

Mohammad H. Soliman, S. Sand, M. Schmidhammer, E. Staudinger

引用次数: 2