改进的基于Spatial WVD和Hough变换的近场信源参量估计及性能分析

Improving Spatial WVD and Hough Transform Based Algorithm for Near-Field Sources Parameter Estimation and Performance Analysis

利用近场信源的一次快拍数据具有近似线性调频信号形式这一特点,将空域—频域联合平滑WVD和边缘检测以及直线拟合技术结合,对边缘检测结果进行Hough变换得到候选点集,并采用最小二乘聚类拟合获得抑制交叉项与噪音影响的初始频率和调频率估计,进而估计出近场信源的波达角和距离参量.理论分析和仿真结果表明,该方法能够显著抑制WVD分布的交叉项,正确拟合信源的原始空域—频域分布,并具有较低的运算复杂度.

The array snap shot is similar with linear frequency modulation （LFM） signal when scatter point located in the near-field,so the near-field sources parameter can be deduced by estimating chirp rate and initial frequency of LFM. A method is proposed propose which using spatial-frequency joined weight WVD for cross-product terms suppressing at first,and taking edge detecting in image domain followed by applying Hough transformation for line detecting and eliminating cross-product terms at the most, then giving the sources parameter estimation, such as direction-of-arrival （DOA） and range by using least square algorithm.Advantages of this approach are that cross-product terms are suppressed markedly and accurate source DOA/rang estimates is obtained without search of a multi-dimensional space.The effectiveness of the algorithm is proved by extensive simulation.