A Comparative Study of BLE-based Fingerprint Localization for Vehicular Application
| Autor: | Zhonghua Zhao, Ji Xiaojun, Pang Xiaofeng, Cao Yiwen, Yang Jian, Lu Xinglong |
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| Rok vydání: | 2018 |
| Předmět: |
Scheme (programming language)
Service (systems architecture) business.industry Computer science Reliability (computer networking) RSS Real-time computing Fingerprint (computing) Automotive industry computer.file_format Probabilistic method Pattern recognition (psychology) business computer computer.programming_language |
| Zdroj: | UPINLBS |
| Popis: | Smartphone-based Passive Entry & Passive Start (PEPS) has become a promising choice for next generation PEPS in automotive industry. Bluetooth Low Energy (BLE) with its low-cost, low power consumption, short delay and high reliability makes smartphone-based PEPS with the potential to replace the existing PEPS. Localization-based Service (LBS) in vehicles requires centimeter-level positioning accuracy and millisecond-Ievel response, which becomes a big challenge for Iocalization scheme and algorithm. This paper studies the critical problem of locating and identifying the interior and exterior ofvehicle based on BLE received signal strength (RSS). A comparative study on interior and exterior positioning in vehicle is presented in this paper by applying deterministic method, probabilistic method and pattern recognition method based on experiments in vehicle. Experiment results show that fingerprint-based probabilistic method gets higher Iocalization accuracy in vehicular application scenario than other methods. |
| Databáze: | OpenAIRE |
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