采用空间极化时频分布的跳频信号多参数联合估计算法
A Joint Estimation Algorithm of Multiple Parameters for Frequency Hopping Signals Using Spatial Polarimetric Time Frequency Distributions

为了在欠定条件下利用信号二维波达方向(2D-DOA)与极化状态进行跳频(FH)网台分选和信号识别、跟踪,提出了一种基于空间极化时频分布(SPTFD)的FH信号多参数联合估计算法。首先利用FH信号时频域特征以及阵列流型建模方法,建立FH信号的极化敏感阵列快拍数据模型;然后通过组合时频分布构造各跳信号的SPTFD矩阵;在此基础上,根据秩损理论对方向和极化信息进行去耦合,利用旋转不变子空间原理估计俯仰角;通过一维搜索和方程求解来估计方位角与极化参数,最终实现了2D-DOA与极化参数的联合估计。新算法无需多维参数寻优和配对,估计精度高。仿真结果表明:该算法能在欠定条件下精确估计FH信号2D-DOA和极化参数;当阵元数为4、信噪比大于6 dB时,空间5个FH信号所有参数的均方根误差均小于1°。
A novel multi？？parameter joint estimation algorithm based on spatial polarimetric time？？frequency distributions (SPTFD) for frequency？？hopping (FH) signals is proposed to sort frequency？？hopping network, identifying and to track signals effectively via the two dimensional direction of arrival (2D-DOA) and polarization of FH signals in underdetermined conditions. Both the time and the frequency features of FH signals are used to derive a data model for its polarization sensitive array based on the modeling method for manifold matrices of arrays; Then a SPTFD matrix for each hop is generated by the combined time？？frequency distribution. The 2D-DOA and the polarization information are then de？？coupled in the light of rank reduction theory, and the elevation angle is estimated via ESPRIT algorithm. Both the azimuth and the polarization are estimated through one？？dimensional search and equation solution, respectively, and the joint estimation of both the 2D-DOA and the polarization of FH signals is completed. The proposed algorithm has good estimate precision without multi parameters optimization or pair？？matching. Simulation results show that the proposed algorithm accurately estimates the 2D-DOA and the polarization of FH signals in underdetermined conditions and that the RMSE of all parameters for five FH signals is less than one degree when there are 4 sensors and the SNR is bigger than 6 dB