基于高斯函数定权的毫米波全息成像算法

Millimeter Wave Holographic Imaging Algorithm Based on Gaussian Function Weighting

毫米波在进行二维横断面成像时,基于变量替换非线性的因素,在波数域等间距的分布在空间域将会显露出不等间距的分布,存在频域数据分布不均匀的情形。现下针对该问题大都采用stolt插值的优化算法进行解决,然而该算法未曾将欧氏距离中不同坐标点对欧氏距离的贡献不等的情形纳入考虑范围内,有鉴于此本文提出一种高斯函数定权的优化算法。通过对所有数据点的欧氏距离进行标准化处理,运用高斯函数分派权值,进行加权处理,借此提高成像精度。仿真分析通过图像熵和脉冲响应宽度两个指标证实了所提算法的可行性。

In the two-dimensional cross-section imaging of millimeter wave,based on the nonlinear factor of variable substitution,the equidistant distribution in the wavenumber domain will show unequal spacing distribution in the spatial domain,and the frequency domain data distribution is uneven.At present,most of the problems are solved by Stolt interpolation optimization algorithm.However,this algorithm does not take into account the different contributions of different coordinate points to Euclidean distance.In view of this,this paper proposes an optimization algorithm of Gaussian function weighting.The Euclidean distance of all data points is standardized,and the Gaussian function is used to assign weights to improve the imaging accuracy.Simulation results show that the proposed algorithm is feasible through image entropy and impulse response width.