Rigorous Performance Evaluation of Smartphone GNSS/IMU Sensors for ITS Applications

被引:44
作者
Gikas, Vassilis [1 ]
Perakis, Harris [1 ]
机构
[1] NTUA, Sch Rural & Surveying Engn, Zografos 15780, Greece
关键词
smartphone; GNSS; MEMS IMU; precision; trueness; intelligent transportation system; SATELLITE; FUSION; FILTER; WIFI;
D O I
10.3390/s16081240
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
With the rapid growth in smartphone technologies and improvement in their navigation sensors, an increasing amount of location information is now available, opening the road to the provision of new Intelligent Transportation System (ITS) services. Current smartphone devices embody miniaturized Global Navigation Satellite System (GNSS), Inertial Measurement Unit (IMU) and other sensors capable of providing user position, velocity and attitude. However, it is hard to characterize their actual positioning and navigation performance capabilities due to the disparate sensor and software technologies adopted among manufacturers and the high influence of environmental conditions, and therefore, a unified certification process is missing. This paper presents the analysis results obtained from the assessment of two modern smartphones regarding their positioning accuracy (i.e., precision and trueness) capabilities (i.e., potential and limitations) based on a practical but rigorous methodological approach. Our investigation relies on the results of several vehicle tracking (i.e., cruising and maneuvering) tests realized through comparing smartphone obtained trajectories and kinematic parameters to those derived using a high-end GNSS/IMU system and advanced filtering techniques. Performance testing is undertaken for the HTC One S (Android) and iPhone 5s (iOS). Our findings indicate that the deviation of the smartphone locations from ground truth (trueness) deteriorates by a factor of two in obscured environments compared to those derived in open sky conditions. Moreover, it appears that iPhone 5s produces relatively smaller and less dispersed error values compared to those computed for HTC One S. Also, the navigation solution of the HTC One S appears to adapt faster to changes in environmental conditions, suggesting a somewhat different data filtering approach for the iPhone 5s. Testing the accuracy of the accelerometer and gyroscope sensors for a number of maneuvering (speeding, turning, etc.,) events reveals high consistency between smartphones, whereas the small deviations from ground truth verify their high potential even for critical ITS safety applications.
引用
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页数:21
相关论文
共 49 条
[11]   Localization and Driving Behavior Classification with Smartphone Sensors in Direct Absence of Global Navigation Satellite Systems [J].
Antoniou, Constantinos ;
Gikas, Vassilis ;
Papathanasopoulou, Vasileia ;
Danezis, Chris ;
Panagopoulos, Athanasios D. ;
Markou, Loulia ;
Efthymiou, Dimitrios ;
Yannis, George ;
Perakis, Harris .
TRANSPORTATION RESEARCH RECORD, 2015, (2489) :66-76
[12]  
Bierlaire M., 2010, 101016 TRANSPOR EC P
[13]   Integrated WiFi/PDR/Smartphone Using an Unscented Kalman Filter Algorithm for 3D Indoor Localization [J].
Chen, Guoliang ;
Meng, Xiaolin ;
Wang, Yunjia ;
Zhang, Yanzhe ;
Tian, Peng ;
Yang, Huachao .
SENSORS, 2015, 15 (09) :24595-24614
[14]  
Chen L, 2012, 2012 UBIQUITOUS POSITIONING, INDOOR NAVIGATION, AND LOCATION BASED SERVICE (UPINLBS)
[15]   Fusion of WiFi, Smartphone Sensors and Landmarks Using the Kalman Filter for Indoor Localization [J].
Chen, Zhenghua ;
Zou, Han ;
Jiang, Hao ;
Zhu, Qingchang ;
Soh, Yeng Chai ;
Xie, Lihua .
SENSORS, 2015, 15 (01) :715-732
[16]   GAFU: Using a Gamification Tool to Save Fuel [J].
Corcoba Magana, V. ;
Munoz-Organero, M. .
IEEE INTELLIGENT TRANSPORTATION SYSTEMS MAGAZINE, 2015, 7 (02) :58-70
[17]  
Dabove P., 2014, INSIDE GNSS, V2014, P35
[18]  
Dickinson J. E., 2012, CURR ISSUES TOUR, V17
[19]   DETERMINING RAIL TRACK AXIS GEOMETRY USING SATELLITE AND TERRESTRIAL GEODETIC DATA [J].
Gikas, V. ;
Daskalakis, S. .
SURVEY REVIEW, 2008, 40 (310) :392-405
[20]  
Gikas V., 2015, P 6 INT C IND POS IN