论文标题
与时钟异步主义的通信系统中基于Kalman滤波器的传感
Kalman Filter-based Sensing in Communication Systems with Clock Asynchronism
论文作者
论文摘要
在本文中，我们提出了一种新型的Kalman滤波器（KF）基于上行链路（UL）关节通信和传感（JCAS）方案，该方案可以大大减少由于基站（BS）和用户设备（UE）之间时钟异步而引起的范围和位置估计误差。时钟异步性会导致时间变化的时间偏移（TO TO）和载体频率偏移（CFO），从而导致上行链路传感的重大挑战。与现有技术不同，我们的方案不需要事先了解UE的位置，并且保留了传感参数估计问题的线性。我们首先估计多径的临界角度（AOA），并使用它们空间过滤CSI。然后，我们提出了一个基于KF的CSI增强剂，该增强子用CFO作为先验信息来利用多普勒对多普勒的估计，以显着抑制空间过滤的CSIS中的时间变化的噪声。随后，我们可以根据KF增强的CSI估算UE的准确范围和散射器。最后，我们确定UE的AOA和范围估计并找到UE，然后使用双静态系统找到愚蠢的散射器。仿真结果验证了提出的方案。所提出方法的定位均方根误差比基准方案低约20 dB。
In this paper, we propose a novel Kalman Filter (KF)-based uplink (UL) joint communication and sensing (JCAS) scheme, which can significantly reduce the range and location estimation errors due to the clock asynchronism between the base station (BS) and user equipment (UE). Clock asynchronism causes time-varying time offset (TO) and carrier frequency offset (CFO), leading to major challenges in uplink sensing. Unlike existing technologies, our scheme does not require knowing the location of the UE in advance, and retains the linearity of the sensing parameter estimation problem. We first estimate the angle-of-arrivals (AoAs) of multipaths and use them to spatially filter the CSI. Then, we propose a KF-based CSI enhancer that exploits the estimation of Doppler with CFO as the prior information to significantly suppress the time-varying noise-like TO terms in spatially filtered CSIs. Subsequently, we can estimate the accurate ranges of UE and the scatterers based on the KF-enhanced CSI. Finally, we identify the UE's AoA and range estimation and locate UE, then locate the dumb scatterers using the bi-static system. Simulation results validate the proposed scheme. The localization root mean square error of the proposed method is about 20 dB lower than the benchmarking scheme.
