Location fingerprint (LF) has been widely applied in indoor positioning. However, the existing studies on LF mostly focus on the fingerprint of WiFi below 6 GHz, bluetooth, ultra wideband (UWB), etc. The LF with millimeter-wave (mmWave) was rarely addressed. Since mmWave has the characteristics of narrow beam, fast signal attenuation and wide bandwidth, etc., the positioning error can be reduced. In this paper, an LF positioning method with mmWave is proposed, which is named as DoA-LF. Besides received signal strength indicator (RSSI) of access points (APs), the fingerprint database contains direction of arrival (DoA) information of APs, which is obtained via DoA estimation. Then the impact of the number of APs, the interval of reference points (RPs), the channel model of mmWave and the error of DoA estimation algorithm on positioning error is analyzed with Cramer-Rao lower bound (CRLB). Finally, the proposed DoA-LF algorithm with mmWave is verified through simulations. The simulation results have proved that mmWave can reduce the positioning error due to the fact that mmWave has larger path loss exponent and smaller variance of shadow fading compared with low frequency signals. Besides, accurate DoA estimation can reduce the positioning error.

中文翻译：

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DoA-LF：具有毫米波的位置指纹定位算法

位置指纹（LF）已广泛应用于室内定位。但是，有关低频的现有研究主要集中在6 GHz以下的WiFi指纹，蓝牙，超宽带（UWB）等上。很少涉及毫米波（mmWave）的低频。由于毫米波具有波束窄，信号衰减快，带宽大等特点，因此可以减少定位误差。本文提出了一种采用毫米波的低频定位方法，称为DoA-LF。指纹数据库除了包含接入点（AP）的接收信号强度指示符（RSSI）外，还包含AP的到达方向（DoA）信息，该信息是通过DoA估计获得的。然后是AP数量，参考点间隔（RP）的影响，利用Cramer-Rao下界（CRLB）分析了毫米波的信道模型和DoA估计算法对定位误差的误差。最后，通过仿真验证了所提出的具有毫米波的DoA-LF算法。仿真结果表明，与低频信号相比，毫米波具有更大的路径损耗指数和较小的阴影衰落变化，可以减小定位误差。此外，准确的DoA估计可以减少定位误差。