摘要
针对现阶段UWB室内定位的测距过程中易出现通信冲突且标签功耗高的问题,提出一种改进的DS-TWR算法。该方法通过一种基于Hash算法的时隙分配方法计算标签和基站的时隙,使每个标签和基站都有唯一时隙,以减少通信过程中标签冲突现象;同时不同于传统TOA测距流程,该方法设置一个主基站,标签只需与主基站进行通信,而从基站只需要进行监听;通过DS-TWR算法来实现标签与主从基站之间的测距过程,最终完成室内定位。实验结果表明,该改进方案可以有效地减少定位通信次数,假设定位基站有N个,改进算法的通信次数约为传统DS-TWR算法的4/3N,且基站越多,减少次数越多,有很强的工程应用价值。通过减少通信次数可以优化标签功耗过高的问题,使标签功耗节省33.3%;针对传统测距算法中通信冲突的问题,在加入Hash算法后,测距过程中基站标签的通信冲突率降低13%,从而使得系统中标签容纳量增加。
In order to solve the problems of more communication conflicts and high label power consumption in the ranging process of UWB indoor positioning at present,an improved DS-TWR algorithm is proposed.This method calculates the time slots of the labels and base stations through a time slot allocation method based on Hash algorithm,so that each label and base station has a unique time slot,so as to reduce the label conflict phenomenon in the communication process.At the same time,different from the traditional TOA ranging process,this method sets up a master base station,the label only needs to communicate with the master base station,and the slave base station only needs to monitor.The DS-TWR algorithm is used to realize the ranging process between the label and the master-slave base station,and finally the indoor positioning is completed.The experimental results show that the improved scheme can effectively reduce the number of positioning communication.Assuming that there are N positioning base stations,the number of communication of the improved algorithm is about 4/3N of that of the traditional DS-TWR algorithm,and the more base stations,the more times to reduce,which has strong engineering application value.By reducing the number of communication,the label power consumption can be optimized and saved by 33.3%.Aiming at the problem of communication conflict in traditional ranging algorithm,after adding Hash algorithm,the communication conflict rate of base station label in the ranging process can be reduced by 13%,thus increasing the capacity of the system.
作者
袁枫
焦良葆
陈楠
顾慧东
YUAN Feng;JIAO Liang-bao;CHEN Nan;GU Hui-dong(Institute of Artificial Intelligence Industry Technology,Nanjing Institute of Technology,Nanjing 211167,China)
出处
《计算机与现代化》
2021年第10期100-106,共7页
Computer and Modernization
