UWB组网定位算法研究

发布时间：2018-04-30 00:15

本文选题：室内定位 + 超宽带　；参考：《广东工业大学》2017年硕士论文

【摘要】：随着科学技术的迅猛发展,人们对位置服务的需求变得越来越多,对位置定位精度的要求越来越高。位置服务产业在智慧城市、救灾减灾、物联网等诸多领域都存在广阔的市场。现如今,全球定位系统GPS已经有效解决了室外的定位问题,同时随着生活水平的提高,人们对部分特殊病人(如:老年痴呆症患者、高危传染病患者以及精神状态异常患者等)的安全监护问题也变得越来越重视,对位置服务的关注重心也开始从室外逐渐转移到室内。由于室内环境复杂,存在大量非视距因素,传统的室内无线定位技术如:射频识别、蓝牙、超声波等,在定位精度上已经很难满足人们的需求。而超宽带技术以其具有的抗干扰能力强、穿透能力强和定位精度高等适合于室内定位环境的优点,在室内人员精确定位上得到人们更多的青睐。本文也将在基于超宽带技术的定位算法上展开研究。首先,本文研究了超宽带信号与室内传输信号模型的特性,并选用IEEE802.15.4a模型作为本文的超宽带信道模型。接着介绍了几种超宽带定位中常用的测距方法和经典定位算法,并对误差的主要来源和对非视距误差的鉴别与抑制方法展开讨论。详细介绍了三种非视距鉴别与抑制算法,分别为:N-Taylor算法、基于几何面积的鉴别算法和基于Chan的残差加权算法。然后,结合双向测距TWR与到达时间差测距TDOA的测距原理,提出一种TWR/TDOA混合测距的方法,该测距方法不需要考虑参考节点与目标节点时钟同步,同时有效减小了TWR测距阶段由节点对信号响应时造成的时延误差问题。在非视距误差问题的处理上,本文在基于几何面积的鉴别算法和基于Chan的残差加权算法的基础上进行适当修改,并通过迭代加权的方式对测距估计值进行修正,直到其结果到达规定的门限值为止,从而降低系统的定位误差。最后,本论文采用MATLAB软件,在室内环境下和视距与非视距环境下分别对经典Chan算法、经典Taylor算法、几何面积鉴别法与本文提出的TWR/TDOA混合定位算法进行了仿真实验与分析,结果表明,无论在视距还是非视距仿真环境下,本论文提出的基于TWR/TDOA的混合定位算法的定位精度更高,定位位置的稳定性更好。
[Abstract]:With the rapid development of science and technology, the demand for location service becomes more and more. Location service industry in intelligent cities, disaster relief, Internet of things and many other fields have a broad market. Nowadays, GPS GPS has effectively solved the problem of outdoor positioning, and with the improvement of living standards, some special patients (such as Alzheimer's disease) have been treated. The safety monitoring of high risk infectious disease patients and patients with abnormal mental state has become more and more important, and the focus of attention on location services has gradually shifted from outdoor to indoor. Because of the complex indoor environment and a large number of non-line-of-sight factors, the traditional indoor wireless positioning technology, such as radio frequency identification, Bluetooth, ultrasonic and so on, has been difficult to meet the needs of people in positioning accuracy. Ultra-wideband (UWB) technology is suitable for indoor positioning environment because of its strong anti-interference ability, strong penetration ability and high positioning accuracy, so it has been more and more popular in precise positioning of indoor personnel. In this paper, the location algorithm based on UWB technology will also be studied. Firstly, the characteristics of UWB signal and indoor transmission signal model are studied, and the IEEE802.15.4a model is chosen as the UWB channel model in this paper. Then, several common ranging methods and classical localization algorithms in UWB location are introduced, and the main sources of errors and the identification and suppression methods of non-line-of-sight errors are discussed. Three kinds of non-line-of-sight discriminant and suppression algorithms are introduced in detail, namely: N-Taylor algorithm, geometric area discriminant algorithm and residual weighting algorithm based on Chan. Then, combining the principle of bidirectional ranging TWR and time-of-arrival ranging (TDOA), a hybrid ranging method of TWR/TDOA is proposed, which does not need to consider the synchronization of reference node and target node clock. At the same time, the delay error caused by the response of the node to the signal in the TWR ranging phase is reduced effectively. Based on the geometric area discriminant algorithm and the residual weighting algorithm based on Chan, the non-line-of-sight error problem is properly modified, and the range estimation is modified by iterative weighting method. The positioning error of the system is reduced until the result reaches the prescribed threshold. Finally, MATLAB software is used to simulate and analyze the classical Chan algorithm, classical Taylor algorithm, geometric area identification algorithm and the TWR/TDOA hybrid localization algorithm proposed in this paper. The results show that the proposed hybrid localization algorithm based on TWR/TDOA is more accurate and more stable in the visual range or non-line-of-sight simulation environment.
【学位授予单位】：广东工业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN925

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