A fusion strategy for reliable vehicle positioning utilizing RFID and in-vehicle sensors
A fusion strategy for reliable vehicle positioning utilizing RFID and in-vehicle sensors
复制标题
利用 RFID 和车载传感器实现可靠车辆定位的融合策略
DOI：
10.1016/j.inffus.2016.01.003
复制
发表时间：
2016-09
影响因子：
18.6
通讯作者：
Zhang Weigong
中科院分区：
文献类型：
--
作者：
Song Xiang;Li Xu;Tang Wencheng;Zhang Weigong
In recent years, RFID has become a viable solution to provide object's location information. However, the RFID-based positioning algorithms in the literature have disadvantages such as low accuracy, low output frequency and the lack of speed or attitude information. To overcome these problems, this paper proposes a RFID/in-vehicle sensors fusion strategy for vehicle positioning in completely GPS-denied environments such as tunnels. The low-cost in-vehicle sensors including electronic compass and wheel speed sensors are introduced to be fused with RFID. The strategy adopts a two-step approach, i.e., the calculation of the distances between the RFID tags and the reader, and then the global fusion estimation of vehicle position. First, a Least Square Support Vector Machine (LSSVM) algorithm is developed to obtain the distances. Further, a novel LSSVM Multiple Model (LMM) algorithm is designed to fuse the data obtained from RFID and in-vehicle sensors. Contrarily to other multiple model algorithms, the LMM is more suitable for current driving conditions because the model probabilities can be calculated according to the operating state of the vehicle by using the LSSVM decision model. Finally, the proposed strategy is evaluated through experiments. The results validate the feasibility and effectiveness of the proposed strategy.
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DOI：
10.3182/20080706-5-kr-1001.01987
发表时间：
2008
期刊：
IFAC Proceedings Volumes
影响因子：
--
作者：
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通讯作者：
H. Ahn;Wonpil Yu
影响因子：
2.3
作者：
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DOI：
10.1109/percom.2012.6199856
发表时间：
2012-03
期刊：
2012 IEEE International Conference on Pervasive Computing and Communications
影响因子：
--
作者：
Lei Yang;Jiannong Cao;Weiping Zhu;Shaojie Tang
通讯作者：
Lei Yang;Jiannong Cao;Weiping Zhu;Shaojie Tang
影响因子：
18.6
作者：
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通讯作者：
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