Adaptive Vehicle Cooperative Positioning System With Uncertain GPS Visibility and Neural Network-based Improved Approach

S. Liu, Dazhi He, Yin Xu, Chao Zhang, Suibin Sun, Dongyu Ru
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引用次数: 2

Abstract

Position accuracy is a key factor to fulfill the requirements of several safety applications of vehicle networking, which will be a prospective application scenario for the Fifth Generation (5G) mobile communication system. In this paper, we present a cooperative localization system, implementing the data fusion of the observation from Received Signal Strength (RSS), Carrier Frequency Offset (CFO) and Global Positioning System (GPS) to enhance the tolerance against the situation of limited GPS visibility. A neural network-based algorithm is also introduced to optimize the accuracy of the cooperative localization system. Results of experiments and simulations demonstrate the improvement on the position stability and accuracy of the integrated system.
GPS可见度不确定的自适应车辆协同定位系统及神经网络改进方法
定位精度是满足车联网多个安全应用需求的关键因素,将成为第五代(5G)移动通信系统的一个有前景的应用场景。本文提出了一种协作定位系统,实现了接收信号强度(RSS)、载波频偏(CFO)和全球定位系统(GPS)观测数据的融合,以增强对GPS能见度有限情况的容忍度。提出了一种基于神经网络的优化协同定位系统精度的算法。实验和仿真结果表明,集成系统的位置稳定性和精度得到了提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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