Wang Lina, Qiu Rui
School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China.
Shunde Graduate School, University of Science and Technology Beijing, Foshan 528300, China.
Sensors (Basel). 2020 Feb 7;20(3):889. doi: 10.3390/s20030889.
The BeiDou navigation satellite system (BDS) developed by China can provide users with high precision, as well as all-weather and real-time positioning and navigation. It can be widely used in many applications. However, new challenges emerge with the development of 5G communication system and Internet of Things (IoT) technologies. The BDS needs to be suitable for the large-scaled terminal scenario and provides higher positioning precision. In this paper, a BeiDou differential positioning method based on IoT and edge computing is proposed. The computational pressure on the data center is offloaded to the edge nodes when the massive positioning requests of IoT terminals need to be processed. To ensure the load balancing of the edge nodes, the resource allocation of the terminal positioning requests is performed with the improved genetic algorithm, thereby reducing the service delay of the entire edge network. Moreover, the optimized unscented Kalman filter based on the edge node (EUKF) algorithm is used to improve the positioning precision of IoT terminals. The results demonstrate that the proposed positioning method has better positioning performance which can provide the real-time positioning service for the large-scale IoT terminals.
中国研发的北斗导航卫星系统（BDS）能够为用户提供高精度以及全天候、实时的定位和导航服务。它可广泛应用于诸多领域。然而，随着5G通信系统和物联网（IoT）技术的发展，新的挑战也随之出现。BDS需要适用于大规模终端场景并提供更高的定位精度。本文提出了一种基于物联网和边缘计算的北斗差分定位方法。当需要处理物联网终端的大量定位请求时，数据中心的计算压力被卸载到边缘节点。为确保边缘节点的负载均衡，采用改进的遗传算法对终端定位请求进行资源分配，从而减少整个边缘网络的服务延迟。此外，基于边缘节点的优化无迹卡尔曼滤波器（EUKF）算法被用于提高物联网终端的定位精度。结果表明，所提出的定位方法具有更好的定位性能，能够为大规模物联网终端提供实时定位服务。
