基于CSI的三维联合参数估计算法

针对商用Wi-Fi设备中由于天线数量和信道带宽有限而导致的到达角(AoA)和飞行时间(ToF)估计精度受限问题，以及现有基于最大似然估计的3维参数估计算法容易收敛于局部最优值，且依次对参数进行估计的方式使参数之间会互相影响的问题，该文提出一种基于Wi-Fi信道状态信息(CSI)的AoA, ToF和多普勒频偏(DFS)的3维联合参数估计算法，以提高参数估计精度和信号分辨能力。首先，通过分析CSI数据，构造包含AoA, ToF和DFS信息的3维矩阵，并对构造的3维矩阵进行降维处理。其次，设计了一种3维空间平滑算法，以消除相干信号对参数估计的影响。最后，利用空间谱估计算法，同时估计出AoA, ToF和DFS 3个参数。实测结果表明该文所提3维联合参数估计算法的参数估计精度和信号分辨能力高于现有的子空间交替期望最大化算法(SAGE)和2维参数估计算法。

3D Parameter Estimation Method Based on CSI

In view of the limitation of the accuracy of the Angle of Arrival (AoA) and Time of Flight (ToF) estimation caused by limited array antennas and channel bandwidth in commodity Wi-Fi devices, and the maximum likelihood estimation algorithm tends sto converge to the local optimal value, and the way to estimate the parameters in turn will affect each other, a three-dimensional joint parameter estimation algorithm for AoA, ToF and Doppler Frequency Shift (DFS) based on Channel State Information (CSI) is proposed to improve parameter estimation accuracy and signal resolution. Firstly, a three-dimensional matrix containing AoA, ToF and DFS information is constructed and the dimensionality of the constructed three-dimensional matrix is reduced. Then, a three-dimensional spatial smoothing algorithm is designed to eliminate the influence of coherent signals on parameter estimation. Finally, the spatial spectrum estimation algorithm is carried out and the three parameters AoA, ToF and DFS are estimated simultaneously. Experimental results show that the accuracy and signal resolution of 3D joint parameter estimation method are higher than Space-Alternating Generalized Expectation maximization(SAGE) and two-dimensional parameter estimation methods.