2010 Ubiquitous Positioning Indoor Navigation and Location Based Service最新文献

UbiSpot - A user trained always best positioned engine for mobile phones UbiSpot -用户训练总是最好的定位引擎的手机

2010 Ubiquitous Positioning Indoor Navigation and Location Based Service Pub Date : 2010-12-03 DOI: 10.1109/UPINLBS.2010.5654313

Tim Schwartz, Christoph Stahl, Christian A. Müller, Valentin Dimitrov, Hao Ji

{"title":"UbiSpot - A user trained always best positioned engine for mobile phones","authors":"Tim Schwartz, Christoph Stahl, Christian A. Müller, Valentin Dimitrov, Hao Ji","doi":"10.1109/UPINLBS.2010.5654313","DOIUrl":"https://doi.org/10.1109/UPINLBS.2010.5654313","url":null,"abstract":"We implemented a positioning engine for mobile phones that can be trained by the users to recognize places as personal landmarks by their wireless communication fingerprint. Our always-best-positioned approach integrates heterogeneous sensor data, such as Bluetooth (BT) device addresses, WLAN MACs, GSM cell ids and GPS coordinates, if available. As an alternative to measuring the signal strength of wireless access points, our positioning engine measures the relative frequency of their appearance and disappearance over time, which closely correlates to their distance. The user can add new places as symbolic names to a hierarchical location model at any time using their mobile phone. For each place, the wireless sensor fingerprint can be trained by the user to define a landmark. Once landmarks have been trained, the positioning engine continuously matches the current sensor profile against the database of learned fingerprints and chooses the most likely place. In case that no BT or WLAN APs are visible, the hierarchical data model can at least derive a higher-level description of the current region based on GSM or GPS as fallback strategy in the sense of being always best positioned. We evaluated the positioning accuracy in our university's lab environment in terms of hits and misses and investigated the effect of various time window sizes for the frequency measurement of the fingerprint. The symbolic location model can be applied for example to adapt the mobile device to different contexts, e.g. automatically mute the ringtone in meeting rooms, trigger location-dependent rules and events, or disclose the current location to friends. (Abstract)","PeriodicalId":373653,"journal":{"name":"2010 Ubiquitous Positioning Indoor Navigation and Location Based Service","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115113362","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: 10

Indoor positioning within a single camera and 3D maps 室内定位内单摄像头和3D地图

2010 Ubiquitous Positioning Indoor Navigation and Location Based Service Pub Date : 2010-12-03 DOI: 10.1109/UPINLBS.2010.5653577

Xun Li, Jinling Wang, Aire Olesk, Nathan Knight, W. Ding

引用次数: 20

Movement tracking of sports team players with wireless sensor network 基于无线传感器网络的运动队队员运动跟踪

2010 Ubiquitous Positioning Indoor Navigation and Location Based Service Pub Date : 2010-12-03 DOI: 10.1109/UPINLBS.2010.5654316

Vinski Bräysy, Jarkko Hurme, Hannu Teppo, T. Korpela, Mikko Karjalainen

引用次数: 8

Overview of methods for visual-aided pedestrian navigation 视觉辅助行人导航方法综述

2010 Ubiquitous Positioning Indoor Navigation and Location Based Service Pub Date : 2010-12-03 DOI: 10.1109/UPINLBS.2010.5653672

L. Ruotsalainen, H. Kuusniemi, Ruizhi Chen

引用次数: 9

The FMCW technology-based indoor localization system 基于FMCW技术的室内定位系统

2010 Ubiquitous Positioning Indoor Navigation and Location Based Service Pub Date : 2010-12-03 DOI: 10.1109/UPINLBS.2010.5654348

Matthias Brugger, T. Christ, Ferdinand Kemeth, Sandor Nagy, Matthias Schäfer, M. Pietrzyk

引用次数: 9

Aiding MEMS IMU with building heading for indoor pedestrian navigation 辅助MEMS IMU进行室内行人导航

2010 Ubiquitous Positioning Indoor Navigation and Location Based Service Pub Date : 2010-12-03 DOI: 10.1109/UPINLBS.2010.5653986

K. Abdulrahim, C. Hide, T. Moore, C. Hill

引用次数: 78

Impact of high-end receivers in a peer-to-peer cooperative localization system 高端接收机在点对点协作定位系统中的影响

2010 Ubiquitous Positioning Indoor Navigation and Location Based Service Pub Date : 2010-12-03 DOI: 10.1109/UPINLBS.2010.5654054

L. Deambrogio, C. Palestini, F. Bastia, Giulio Gabelli, G. Corazza, J. Samson

引用次数: 9

Low cost vision-aided IMU for pedestrian navigation 用于行人导航的低成本视觉辅助IMU

2010 Ubiquitous Positioning Indoor Navigation and Location Based Service Pub Date : 2010-12-03 DOI: 10.1109/UPINLBS.2010.5653658

C. Hide, T. Botterill, M. Andreotti

引用次数: 69

Rao-Blackwellized particle filter for pattern matching indoor localisation rao - blackwelzed粒子滤波模式匹配室内定位

2010 Ubiquitous Positioning Indoor Navigation and Location Based Service Pub Date : 2010-12-03 DOI: 10.1109/UPINLBS.2010.5654321

S. Wibowo, M. Klepal

{"title":"Rao-Blackwellized particle filter for pattern matching indoor localisation","authors":"S. Wibowo, M. Klepal","doi":"10.1109/UPINLBS.2010.5654321","DOIUrl":"https://doi.org/10.1109/UPINLBS.2010.5654321","url":null,"abstract":"Pattern matching localisation based on Received Signal Strength Indication (RSSI) is widely implemented in the Wireless Local Area Network (WLAN). This implementation is commonly with a filtering method to achieve better location estimation accuracy. A Kalman filter (KF) is an optimal filter, if requirements on linear/Gaussian state space model are met. Otherwise, a particle filter (PF) should be used to deal with nonlinear/non-Gaussian state space model. However, in the real situation especially in the localisation field, the state space model may be linear/Gaussian and nonlinear/non-Gaussian. Therefore, there should be a filtering method that can accommodate both linear/Gaussian and nonlinear/non-Gaussian state space model such as Rao Blackwellized particle filter (RBPF). RBPF implemented in the pattern matching localisation system is described and its performance is compared against KF and PF. Those three filtering methods are evaluated in the test bed. To the best of our knowledge, implementing RBPF and performance comparison against KF and PF in the pattern matching indoor localisation in WLAN environment have never been published before.","PeriodicalId":373653,"journal":{"name":"2010 Ubiquitous Positioning Indoor Navigation and Location Based Service","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124542082","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: 3

Advanced MDS based localization algorithm for location based services in Wireless Sensor Network 无线传感器网络中基于位置服务的高级MDS定位算法

2010 Ubiquitous Positioning Indoor Navigation and Location Based Service Pub Date : 2010-12-03 DOI: 10.1109/UPINLBS.2010.5654301

B. Wei, Wu Chen, X. Ding

{"title":"Advanced MDS based localization algorithm for location based services in Wireless Sensor Network","authors":"B. Wei, Wu Chen, X. Ding","doi":"10.1109/UPINLBS.2010.5654301","DOIUrl":"https://doi.org/10.1109/UPINLBS.2010.5654301","url":null,"abstract":"Wireless Sensor Networks (WSNs) are increasingly being used for various information collection in the future. For many applications, a large number of sensors in an active wireless network are more effective and preferable to a few expensive wireless sensors. Location discovery of sensor nodes after they have been deployed is known as a challenge, especially for moving sensors. Algorithms based on radio signal strength indication are considered as the lowest cost method to solve localization problem. But in practice, the accuracy of signal strength indication algorithm varies with the average distances between wireless nodes - the nearer, the better. This paper describes a new integrated dynamic localization algorithm, based on Received Signal Strength Indication (RSSI) and Multidimensional Scaling (MDS) algorithm. In this concept, signals with RSSI values among beacon nodes could help to generate a real time 2D map of the network by self iterations. Unknown nodes use the map to determine their locations in this region. A software simulator is created to test the performance of the algorithm, and practical experiments also show the development of localization accuracy and efficiency.","PeriodicalId":373653,"journal":{"name":"2010 Ubiquitous Positioning Indoor Navigation and Location Based Service","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116460593","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: 10