基于DS-TWR的室外远距离定位算法优化  

Optimization of Outdoor Long-range Localization Algorithm Based on DS-TWR

作　　者：刘唯 尹磊 沈子阳 LIU Wei;YIN Lei;SHEN Ziyang(College of Mechanical Engineering,Nanjing University of Science and Technology,Nanjing 210094,China)

机构地区：[1]南京理工大学机械工程学院,南京210094

出　　处：《自动化与仪表》2023年第10期62-66,71,共6页Automation & Instrumentation

摘　　要：现阶段基于双边双向测距(DS-TWR)算法的超宽带(UWB)定位系统在多标签的环境下通信冲突率高,应用在长距离下会产生较大的测距误差,针对这2个问题,该文提出了改进算法。在通信方案方面,通过Hash算法对标签进行分布,以确定标签应该与哪个基站进行通信,再由基站统一回复,减少基站发送消息的次数。在测距方面,提出一种自适应卡尔曼滤波算法,以提高测距的精度。实验结果表明,通信的冲突率下降了36%,测距的精度与无滤波的情况下相比,误差减小了76%。Currently,the UWB positioning system utilizing the DS-TWR algorithm has a high communication conflict rate in multi-tag environments.It can generate significant ranging errors when used at long distances.An enhanced algorithm has been proposed in order to tackle these issues.Regarding communication,the tags are distributed using a Hash algorithm to determine with which base station they should communicate.The base stations reply uniformly to reduce the number of messages.Regarding ranging,an adaptive Kalman filtering algorithm is proposed to improve the precision of the measurements.The results indicate a reduction in the communication conflict rate by approximately 36%and a decrease in the ranging error by around 76%compared to the situation without filtering.

关 键 词：超宽带 双边双向测距 HASH算法 卡尔曼滤波 

分 类 号：TP274[自动化与计算机技术—检测技术与自动化装置]