Towards Robust Crowdsourcing on Wireless and Environmental Localization Maps - A GNSS and Multi-Sensor Integration Approach
(0) Crowdsourcing-based localization signal (e.g., wireless signal and environmental signal) database updating is becoming a trend for low-cost location-based service (LBS) and location-enhanced internet of things (L-IoT) applications. This paper proposes a crowdsourcing-based localization framework that updates both wireless (e.g., WiFi) and environmental (e.g., magnetic) signal maps autonomously. Compared to the existing indoor localization methods that do not involve GNSS, this paper introduces GNSS data as constraints for the optimization of crowd-sourced dead-reckoning (DR) solutions. Furthermore, to alleviate the issue that multiple localization signals do not interact, this paper combines multiple signals to a multi-source localization database, which is convenient and effective to be used to enhance localization. Through the use of the generated multi-source database for localization, there was an accuracy improvement of approximately 20 % compared to the state-of-the-art DR/Wireless/Magnetic integration solution.
crowdsourcing location-based services internet of things fingerprinting dead-reckoning magnetic matching
You Li Zhouzheng Gao Zhe He Peng Zhang Chuang Shi Naser El-Sheimy
Department of Geomatics Engineering, University of Calgary, 2500 University Dr NW, Calgary, AB T2N 1 School of Land Science and Technology, China University of Geosciences (Beijing), 29 Xueyuan Road, B State Key Laboratory of Surveying, Mapping and Remote Sensing, Wuhan University, 129 Luoyu Road, Wuh School of Electronic and Information Engineering, Beihang University, 37 Xueyuan Road, Beijing, Chin
国内会议
北京
英文
1-11
2019-05-01（万方平台首次上网日期，不代表论文的发表时间）