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| device-clustering algorithm in crowdsourcing-based localization | |
| Cheng Huang; Luo Hai-Yong; Zhao Fang | |
| 2012 | |
| Source | Journal of China Universities of Posts and Telecommunications
 |
| ISSN | 1005-8885 |
| Volume | 19Issue:SUPPL. 2Pages:114-121 |
| English Abstract | Device heterogeneity significantly degrades the localization performance of fingerprinting-based localization, especially in the crowdsourcing-based positioning system. Although manual calibration can reduce positional error, the adjustment overhead is extremely heavy and to maintain ever-increasing device types is overly laborious. In this paper, we propose a novel device-clustering algorithm to operate the positioning system based on macro device-cluster (DC) rather than natural device. In this way, the system maintains less device types and the localization accuracy is improved obviously. The experimental result of different combination indicates the optimal operating flow is to combine DC and kernel density estimator when the tracking device is known and add the linear transformation phase when device is unknown. © 2012 The Journal of China Universities of Posts and Telecommunications.; Device heterogeneity significantly degrades the localization performance of fingerprinting-based localization, especially in the crowdsourcing-based positioning system. Although manual calibration can reduce positional error, the adjustment overhead is extremely heavy and to maintain ever-increasing device types is overly laborious. In this paper, we propose a novel device-clustering algorithm to operate the positioning system based on macro device-cluster (DC) rather than natural device. In this way, the system maintains less device types and the localization accuracy is improved obviously. The experimental result of different combination indicates the optimal operating flow is to combine DC and kernel density estimator when the tracking device is known and add the linear transformation phase when device is unknown. © 2012 The Journal of China Universities of Posts and Telecommunications. |
| Indexed Type | EI |
| Keyword | Navigation Systems |
| Department | (1) Software School Beijing University of Posts and Telecommunications Beijing 100876 China; (2) Institute of Computing Technology Chinese Academy of Sciences Beijing 100876 China |
| Language | 英语 |
| Content Type | 期刊论文 |
| URI | http://ir.iscas.ac.cn/handle/311060/15442 |
| Collection | 中国科学院软件研究所 |
| Recommended Citation GB/T 7714 | Cheng Huang,Luo Hai-Yong,Zhao Fang. device-clustering algorithm in crowdsourcing-based localization[J]. Journal of China Universities of Posts and Telecommunications,2012,19(SUPPL. 2):114-121. |
| APA | Cheng Huang,Luo Hai-Yong,&Zhao Fang.(2012).device-clustering algorithm in crowdsourcing-based localization.Journal of China Universities of Posts and Telecommunications,19(SUPPL. 2),114-121. |
| MLA | Cheng Huang,et al."device-clustering algorithm in crowdsourcing-based localization".Journal of China Universities of Posts and Telecommunications 19.SUPPL. 2(2012):114-121. |
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