OFDM子载波相位差TOA测距方法的抗多径性能

The multipath mitigation performance of OFDM subcarrier phase difference TOA ranging method

目前,大量物联网终端都具有Wi-Fi或蜂窝网接入能力。Wi-Fi网络或蜂窝网提供通信功能的同时确定终端在室内的位置的研究得到学术界以及工业界的重视。但是,高精度定位通常需要高精度测距的支持,而受制于严重的多径反射,室内的测距精度有限。而目前广泛部署的Wi-Fi和蜂窝网均使用正交频分复用(OFDM)信号,其用于测距时的抗多径能力却没有得到系统研究。所以,文章首先分析研究了基于相邻子载波相位差的到达时间(TOA)测距方法,然后采用室内环境的IEEE 802.11信道模型,对基于Zadoff-Chu导频序列的相位差方法的性能进行了计算机仿真,验证了该方法具有线性拟合方法所不具有的抗多径能力。然后,我们使用WARP软件无线电平台在两种实际室内环境中进行相邻子载波相位差方法的测距实验。结果表明在带宽为20 MHz及测量范围为2-7米的情况下,该方法的平均TOA估计精度分别达到0.4米和0.49米,显示了较强的抗多径能力,表明该方法在室内定位中具有较大的应用潜力。

At present, a large number of terminals in the IoT have the ability to access Wi-Fi or cellular networks, so it is very attractive to determine the locations of terminals while communicating using Wi-Fi or cellular networks. The research on how to determine the location of the terminal in the room while providing the communication function of Wi-Fi network or cellular network has been paid attention by the academia and the industry. However, High-accuracy positioning usually requires the support of high-precision distance measurement, and the indoor ranging accuracy is limited by severe multi-path reflections. Currently widely deployed Wi-Fi and cellular networks use Orthogonal Frequency Division Multiplexing （OFDM） signals, and their anti-multipath capability has not been studied systematically. So this article studies Time of arrival （TOA） estimation scheme based on phase difference of adjacent subcarriers of OFDM signals, and then uses the IEEE 802.11 channel model for indoor environments and explore the performance of the adjacent subcarrier phase difference （ASPD） method with a ZadoffChu sequence through simulation, and the ASPD method is superior to the line fitting method. Then, we use the WARP software radio platform to perform ranging experiments of ASPD method in two actual indoor environments. The results show that when the bandwidth is 20 MHz and the measuring range is 2-7 m, the average TOA estimation accuracy of the method reaches 0.4 meters and 0.49 meters respectively, which shows a strong anti-multipath capability, and therefore has a great application potential in indoor positioning.