基于极化时频分布的改进DOA估计算法

针对雷达回波信号波达方向估计精度差和时频分析方法运算量大的问题,以极化敏感阵列为模型,结合时频分析方法,充分利用回波信号的空域、时频域和极化域信息,对雷达回波信号进行更准确的估计,并简化其计算量。分析基于空间极化时频分布的多重信号分类(MUSIC)和旋转不变子空间(ESPRIT)算法,并结合两者的优缺点提出了一种改进算法。改进算法用极化时频ESPRIT算法对来波信号确定大致的方位角,以每个方位角为中心确定一个小角度范围,在此范围内用MUSIC算法进行谱峰搜索,得到较准确的波达方向(DOA)估计值,在确保DOA估计精度的基础上节省大部分运算时间。仿真试验验证了该改进算法的有效性。

Improved Algorithm for DOA Estimation Based on Spatial Polarimetric Time-Frequency Distribution

To solve the problem of poor direction of arrival (DOA) estimation accuracy of radar echo signals and heavy computation of time-frequency analysis method, taking polarization sensitive array as the model, and combined with time-frequency analysis method, this paper makes full use of the spatial, time-frequency and polarized domain information of signals to estimate the radar echo signals more accurately and reduce the computation burden. The multiple signal classification (MUSIC) and estimation of signal parameters via rotational in-variance techniques (ESPRIT) algorithms based on spatial polarimetric time-frequency distribution are studied, and the improved algorithm is proposed in consideration of advantages and disadvantages of both algorithms. The improved algorithm roughly estimates azimuth angles of signals with the polarized time-frequency ESPRIT algorithm, and then determines a small scope centered on each azimuth. Within the scope, a more accurate DOA estimation value is obtained by spectral peak search with MUSIC algorithm. It can save a large amount of computation time on the basis of accurate DOA estimation. The effectiveness of the improved algorithm is verified by the simulation test.