2017 International Conference on Localization and GNSS (ICL-GNSS)最新文献

Investigation of the RUFRIS method with GNSS and total station for leveling 基于GNSS和全站仪的RUFRIS平准方法研究

2017 International Conference on Localization and GNSS (ICL-GNSS) Pub Date : 2017-06-27 DOI: 10.1109/ICL-GNSS.2017.8376251

Mohammad Amin Alizadeh Khameneh, A. Jensen, M. Horemuz, J. Andersson

引用次数: 7

Adaptive real-time dual-mode filter design for seamless pedestrian navigation 无缝行人导航的自适应实时双模滤波器设计

2017 International Conference on Localization and GNSS (ICL-GNSS) Pub Date : 2017-06-27 DOI: 10.1109/ICL-GNSS.2017.8376257

Pekka Peltola, C. Hill, T. Moore

{"title":"Adaptive real-time dual-mode filter design for seamless pedestrian navigation","authors":"Pekka Peltola, C. Hill, T. Moore","doi":"10.1109/ICL-GNSS.2017.8376257","DOIUrl":"https://doi.org/10.1109/ICL-GNSS.2017.8376257","url":null,"abstract":"Seamless navigation requires that the mobile device is capable of offering a position solution both indoors and outdoors. Novel seamless navigation system design was implemented and tested to achieve this aim. The design consists of general navigation system framework blocks and of the necessary interface agreements between the blocks. This approach enables plug-and-play style design of modules. The implementation used four preselected key technologies. Microstrain 3DM-GX4-45 foot-mounted inertial measurement unit sensor data was fused together with the u-blox GNSS receiver positions outdoors. Context sensitive inference engine enabled the fusion of position updates indoors from the De-cawave TREK1000 Ultra WideBand ranging kit and from the 6 Kontakt.io/Raspberry Pi anchor-based Bluetooth low energy fingeprinting system. Novel dual-mode filter design uses a particle filter and the pentagon buffer enhanced Kalman filter in the position solution derivation. Depending on the map and the walls in the environment and on the quality of position updates, the implemented control logic employs the most fit filter for the current context. Computational power is now focussed, when particle filter is needed. The novel pentagon buffer enhanced Kalman filter is 10 times faster, allowing power saving when situation is not too critical. Moreover, the buffer provides position updates by interacting with the map and helps to correct the position solution. The navigation system is seamless according to the tests conducted around and within the Nottingham Geospatial building. No user input is needed for smooth transition from outdoors to indoors and vice versa. The system achieves an accuracy of 2.35 m outdoors and 1.4 m indoors (95% of error). Inertial system availability was continuous, while GNSS was available outdoors and BLE and UWB indoors.","PeriodicalId":330366,"journal":{"name":"2017 International Conference on Localization and GNSS (ICL-GNSS)","volume":"1 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":"130438708","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: 7

A segmentation-based matching algorithm for magnetic field indoor positioning 一种基于分段匹配的磁场室内定位算法

2017 International Conference on Localization and GNSS (ICL-GNSS) Pub Date : 2017-06-27 DOI: 10.1109/ICL-GNSS.2017.8376237

Yichen Du, T. Arslan

{"title":"A segmentation-based matching algorithm for magnetic field indoor positioning","authors":"Yichen Du, T. Arslan","doi":"10.1109/ICL-GNSS.2017.8376237","DOIUrl":"https://doi.org/10.1109/ICL-GNSS.2017.8376237","url":null,"abstract":"Magnetic field-based location fingerprinting techniques are emerging technologies used in indoor navigation that take advantage of magnetic field anomalies. k Nearest Neighbours (kNN) is one of the general matching algorithms that is widely used in fingerprint-based indoor positioning systems to estimate the location of users. However, the standard kNN algorithm always visits all the data in a database in order to take the appropriate nearest k neighbours into account while calculating the estimated location. One of the key disadvantages associated with kNN is the fact that computational complexity is quite large. In order to deal with this issue and improve the precision of this method, this paper proposes the use of a new method called Segmentation-based kNN algorithm. This approach conducts suitable selection and partitioning on the target positioning area before calculating the kNN. We have calculated the accuracy rate of the proposed algorithm and compared it with standard kNN algorithm, and the results show that the proposed algorithm performs better than the kNN algorithm with an improvement of 9.24% in average accuracy.","PeriodicalId":330366,"journal":{"name":"2017 International Conference on Localization and GNSS (ICL-GNSS)","volume":"31 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":"125457993","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: 5

Parametrization and prediction of EGNOS GIVD values EGNOS GIVD值的参数化与预测

2017 International Conference on Localization and GNSS (ICL-GNSS) Pub Date : 2017-06-27 DOI: 10.1109/ICL-GNSS.2017.8376258

M. Mäkelä, S. Ali-Löytty, Philipp Müller, R. Piché

引用次数: 0

High definition map-based vehicle localization for highly automated driving: Geometric analysis 基于地图的高度自动驾驶车辆定位:几何分析

2017 International Conference on Localization and GNSS (ICL-GNSS) Pub Date : 2017-06-27 DOI: 10.1109/ICL-GNSS.2017.8376252

Shuran Zheng, Jinling Wang

{"title":"High definition map-based vehicle localization for highly automated driving: Geometric analysis","authors":"Shuran Zheng, Jinling Wang","doi":"10.1109/ICL-GNSS.2017.8376252","DOIUrl":"https://doi.org/10.1109/ICL-GNSS.2017.8376252","url":null,"abstract":"High definition (HD) map is a critical part of highly automated driving (HAD) technology and shows potential for high precision vehicle localization when GNSS signals are not available. The current study of using HD map for localiz ation is mostly based on Simultaneous Localization and Mapping (SLAM) technique, which requires high computing power, huge storage space, and quick data transmission ability. Therefore, a study of a new HD map based vehicle localization method which requires less computation is necessary. Geometry is one key component that affects the quality of localization, including accuracy, reliability, and separability. Analysing the geometry can provide reference for designing a localization system to meet the quality requirement of HAD, but is rarely studied. This paper aims to design a high precision and reliable localization system using HD map as a sensor, and the influence of geometry is also explored. Geometric strength is evaluated under different scenarios considering three factors, including feature distribution type, feature number, and distance between vehicle and feature. The results show Minimum Detectable Bias (MDB) and Minimal Separable Bias (MSB) are mostly affected by feature number and distance between vehicle and feature. Randomly distribution, more detected features and close distance between the host vehicle and the features may all contribute to good quality of vehicle position estimation.","PeriodicalId":330366,"journal":{"name":"2017 International Conference on Localization and GNSS (ICL-GNSS)","volume":"35 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":"116501900","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: 21

Monte Carlo localization algorithm for indoor positioning using Bluetooth low energy devices 蒙特卡罗定位算法用于室内低功耗蓝牙设备的定位

2017 International Conference on Localization and GNSS (ICL-GNSS) Pub Date : 2017-06-27 DOI: 10.1109/ICL-GNSS.2017.8376248

Xiaoyue Hou, T. Arslan

{"title":"Monte Carlo localization algorithm for indoor positioning using Bluetooth low energy devices","authors":"Xiaoyue Hou, T. Arslan","doi":"10.1109/ICL-GNSS.2017.8376248","DOIUrl":"https://doi.org/10.1109/ICL-GNSS.2017.8376248","url":null,"abstract":"This paper presents a technique for indoor localization using the Monte Carlo localization (MCL) algorithm. The MCL was upgraded from Markov localization, with both belonging to the family of probabilistic approaches. Throughout the last decade, laser rangefinders and gyroscopes have been applied to MCL-based robotic localization systems with remarkable success. However, the utilization of MCL-based indoor localization for mobile devices, by applying Bluetooth low energy (BLE) sensors, is still being researched. In this paper, we present a technique that utilizes MCL that exploits two sensors, namely, the accelerometer and compass, with commonly deployed BLE beacons to localize people with mobile devices indoors. Experimental results illustrate that, by applying MCL with BLE beacons using an accelerometer and compass, the error of the calculated coordinates for the user position is less than 1 m in line of-sight (LOS) environments, while in a complex non-LOS environment, the average error is 3 m. Meanwhile, the proposed MCL system does not demand a high deployment density of BLE beacons compared with triangulation and trilateration-based indoor positioning algorithms.","PeriodicalId":330366,"journal":{"name":"2017 International Conference on Localization and GNSS (ICL-GNSS)","volume":"54 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":"121448457","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: 37

Coarse to fine global RGB-D frames registration for precise indoor 3D model reconstruction 粗到细的全局RGB-D框架配准，用于精确的室内3D模型重建

2017 International Conference on Localization and GNSS (ICL-GNSS) Pub Date : 2017-06-27 DOI: 10.1109/ICL-GNSS.2017.8376250

W. Darwish, Wenbin Li, Shengjun Tang, Wu Chen

引用次数: 4

Optimizing matched filters for GNSS receivers GNSS接收机匹配滤波器优化

2017 International Conference on Localization and GNSS (ICL-GNSS) Pub Date : 2017-06-27 DOI: 10.1109/ICL-GNSS.2017.8376238

V. Eerola

引用次数: 0

Dealing with network changes in cellular fingerprint positioning systems 蜂窝指纹定位系统中网络变化的处理

2017 International Conference on Localization and GNSS (ICL-GNSS) Pub Date : 2017-06-27 DOI: 10.1109/ICL-GNSS.2017.8376255

Andrea Viel, P. Gallo, A. Montanari, Donatella Gubiani, A. D. Torre, Federico Pittino, C. Marshall

引用次数: 4

Peer-to-peer cooperative GNSS-based localization for stationary reference nodes in wireless sensor networks 基于点对点协同gnss的无线传感器网络静止参考节点定位

2017 International Conference on Localization and GNSS (ICL-GNSS) Pub Date : 2017-06-27 DOI: 10.1109/ICL-GNSS.2017.8376241

I. Hakala, Jari Luomala

引用次数: 2