Smart environment sensing and other applications play a more and more important role along with the rapid growth of device-free sensing-based services, and extracting parameters contained in channel state information (CSI) accurately is the basis of these applications. However, antenna arrays in wireless devices are all planar arrays whose antenna spacing does not meet the spatial sampling theorem while the existing parameter estimation methods are almost based on the array satisfying the spatial sampling theorem. In this paper, we propose a parameter estimation algorithm to estimate the signal parameters of angle of arrival (AoA), time of flight (ToF), and Doppler frequency shift (DFS) based on the service antenna array, which does not satisfy the spatial sampling theorem. Firstly, the service antenna array is mapped to a virtual linear array and the array manifold of the virtual linear array is calculated. Secondly, the virtual linear array is applied to estimate the multi-dimensional parameters of the signal. Finally, by calculating the geometric relationship between the service antenna and the virtual linear array, the parameters of the signal incident on the service antenna can be obtained. Therefore, the service antenna can not only use the communication channel for information communication, but also sense the surrounding environment and provide related remote sensing and other wireless sensing application services. Simulation results show that the proposed parameter estimation algorithm can accurately estimate the signal parameters when the array antenna spacing does not meet the spatial sampling theorem. Compared with TWPalo, the proposed algorithm can estimate AoA within 3^∘, while the error of ToF and DFS parameter estimation is within 1 ns and 1 m/s.

随着基于无设备传感的服务的快速增长，智能环境传感和其他应用程序扮演着越来越重要的角色，准确提取信道状态信息（CSI）中包含的参数是这些应用程序的基础。然而，无线设备中的天线阵列都是平面阵列，其天线间距不满足空间采样定理，而现有的参数估计方法几乎都是基于满足空间采样定理的阵列。在本文中，我们提出了一种基于服务天线阵列的参数估计算法，用于估计到达角（AoA），飞行时间（ToF）和多普勒频移（DFS）的信号参数，该算法不能满足空间采样定理。首先，将服务天线阵列映射到虚拟线性阵列，并计算虚拟线性阵列的阵列流形。其次，将虚拟线性阵列应用于估计信号的多维参数。最后，通过计算服务天线和虚拟线性阵列之间的几何关系，可以获得入射在服务天线上的信号的参数。因此，服务天线不仅可以使用通信信道进行信息通信，还可以感知周围环境，并提供相关的遥感和其他无线传感应用服务。仿真结果表明，当阵列天线间距不满足空间采样定理时，所提出的参数估计算法可以准确估计信号参数。^∘，而ToF和DFS参数估计的误差在1 ns和1 m / s之内。