A Hybrid Localization Algorithm Based on TOF and TDOA for Asynchronous Wireless Sensor Networks
A Hybrid Localization Algorithm Based on TOF and TDOA for Asynchronous Wireless Sensor Networks
复制标题
基于TOF和TDOA的异步无线传感器网络混合定位算法
DOI：
10.1109/access.2019.2951140
复制
发表时间：
2019
期刊：
影响因子：
3.9
通讯作者：
Hui Xiong
中科院分区：
文献类型：
--
作者：
Tan Wang;Hui Xiong
精度和能耗是定位系统的两个至关重要的评估标准。单一技术使用的定位算法由于其局限性可能无法平衡精度和功耗问题。此外，现有的组合定位方法的性能并不令人满意。在本文中，考虑到相对时钟偏差，我们研究了对称双面双向测距（SDS-TWR）方法中的偏置飞行时间（TOF）补偿问题。我们首先估计传感器节点之间的相对时钟偏差，以提高测距结果的准确性。然后结合到达时间差（TDOA）算法，减少标签（需要定位的节点）侧的发送和接收次数。最后通过牛顿迭代法确定标签位置。仿真验证了我们的理论分析，结果表明，与 C-TDOA 方法相比，我们提出的混合定位算法显着提高了定位精度。此外，所提出的混合定位算法可以克服传统基于TOF的算法中功耗高的缺点。
Accuracy and energy consumption are two crucial assessment standards for localization systems. The positioning algorithm used in a single technique may not balance the accuracy and power problem due to its limitations. Moreover, the performance of the existing combined localization method is unsatisfactory. In this paper, taking the relative clock skew into account, we investigate the biased time-of-flight (TOF) compensation problem in the symmetric double-sided two-way ranging (SDS-TWR) method. We first estimate the relative clock skew among sensor nodes to improve the accuracy of the ranging result. We then combine with the time-difference-of-arrival (TDOA) algorithm and reduce the number of transmissions and receptions on the tag (a node that needs to be located) side. Finally, the tag location is determined by Newton’s iteration method. A simulation is implemented to validate our theoretical analysis and the results show that our proposed hybrid localization algorithm improves the locating accuracy significantly, compared with that of the C-TDOA method. Furthermore, the proposed hybrid localization algorithm can overcome the shortcoming of high power cost in the conventional TOF-based algorithm.
登录
查看更多内容
影响因子：
2.5
作者：
S. Kay
通讯作者：
S. Kay
影响因子：
5.4
作者：
Vaghefi, Reza Monir;Buehrer, R. Michael
通讯作者：
Buehrer, R. Michael
影响因子：
10.4
作者：
Wang, Yue;Ho, K. C.
通讯作者：
Ho, K. C.
基于RSSI空间分辨率不均匀的室内定位新加权算法
影响因子：
3.9
作者：
Xue, Weixing;Hua, Xianghong;Cheng, Kai
通讯作者：
Cheng, Kai
影响因子：
3.9
作者：
Lutao Liu;Huan-Chang Liu
通讯作者：
Lutao Liu;Huan-Chang Liu