跳频信号2D-DOA与极化参数的欠定估计

为在欠定条件下估计跳频(frequency hopping,FH)信号二维波达方向(two dimensional direction of arrival,2D-DOA)和极化参数,从而有效辅助FH网台分选和信号识别、跟踪等,提出基于空间极化时频分析的联合估计算法.在建立FH信号极化敏感阵列快拍数据模型基础上,推导空间极化时频分布(spatial polarimetric time frequency distributions,SPTFD)的线性时频扩展形式SPSTFT,同时给出一种组合时频分布方法定位各跳(hop)信号在时频面上的自项区域,据此构造各hop的SPTFD和SPSTFT矩阵.利用SPSTFT/SPTFD矩阵中蕴含的信源极化-空域特征信息采取两种不同方法估计2D-DOA和极化参数.新算法无需多维参数寻优和配对,计算量小.仿真结果表明,本算法能在欠定条件下有效估计FH信号2D-DOA和极化参数,SPTFD矩阵法估计精度高,并能处理发生频率碰撞的hop.

Underdetermined estimation of 2D-DOA and polarization for frequency hopping signals

In order to sort frequency-hopping networks, identify and track signals effectively, an novel joint estimation algorithm based on spatial polarimetric time-frequency analysis is proposed as the solution for the two dimensional direction of arrival (2D-DOA) and polarization estimation of Frequency Hopping (FH) signals in underdetermined condition. First, the data model for polarization sensitive array of FH signals is built. On this basis, the SPSTFT, the extendable form of spatial polarimetric time frequency distributions, is derived. Meanwhile, a new combined time-frequency(TF) analysis method is presented to locate the auto term region of each hop in the TF plane. Consequently, the SPTFD and SPSTFT matrix for each hop is generated. Finally, depending on the spatial and polarization information getting from SPTFD and SPSTFT matrix, the 2D-DOA and polarization are estimated by two different methods. With splendid estimation precision, this novel method requires less computation burden without multiple-parameter optimization and pair-matching. Simulation results show that the proposed algorithm could estimate 2D-DOA and polarization in underdetermined condition effectively, and the SPTFD matrix method has high estimation accuracy.Besides, the collision hop could be processed.