小波分析在毫米波综合孔径近场成像中的应用
The Application of Wavelet Analysis for the Near-Field Millimeter Wave Synthetic Apeture Imaging

作者: 张育浩 , 王海辉 , 李超 :北京航空航天大学数学与系统科学学院,北京;

关键词: 毫米波成像近场小波阈值去噪–滤波算法Millimeter Wave Imaging Near-Field Wavelet Thresholding-Filtering Algorithm

摘要: 毫米波综合孔径的成像技术在近场成像中有着广阔的应用前景,无需机械扫描,可稀疏阵列,具有较高的空间分辨率。毫米波综合孔径近场可视度模型可转化为V=AR+n,这是一个欠定方程组,解不唯一,且含有噪声。综合小波阈值去噪算法及均值滤波在去噪方面的优点,提出了一种改进的小波阈值去噪-滤波算法,并且改进了传统小波阈值去噪中的软、硬阈值法。通过将基于偏微分方程的正则化方法及改进的小波阈值去噪-滤波算法应用在一个实际的近场仿真实验中,比较发现改进的小波阈值去噪-滤波算法要优于基于偏微分方程的正则化方法。

Abstract: Millimeter wave imaging technology using synthetic aperture has broad application prospects in the near field. It has high spatial resolution without mechanical scanning. Near-field millimeter wave synthetic aperture visibility model can be transformed into V=AR+n , this is an underde-termined equation, the solution is not unique, and it contains noise. An improved wavelet thre-sholding-filtering algorithm combining wavelet thresholding algorithm’s advantages and mean filtering’s advantages in terms of de-noising is presented. The method improves traditional soft and hard threshold method. At the last, we make the regularization method based on partial differential equations and the improved wavelet thresholding-filtering algorithm used in an actual near-field simulation experiment. By comparison, we find that the imaging results of the improved algorithm are better than the regularization method based on PDE.

文章引用: 张育浩 , 王海辉 , 李超 (2017) 小波分析在毫米波综合孔径近场成像中的应用。 应用数学进展, 6, 62-68. doi: 10.12677/AAM.2017.61008

参考文献

[1] 姚现勋, 尚晓舟, 苗俊刚, 李志平. 综合孔径辐射计偏微分方程近场图像反演算法[J]. 北京航空航天大学学报, 2015, 41(2): 267-272.

[2] 王科举. 毫米波综合孔径辐射计近场成像研究[D]: [硕士学位论文]. 武汉: 华中科技大学: 电子与通讯工程, 2011.

[3] Tanner, A.B., Lambrigsten, B.H., Gaier, T.M., et al. (2006) Near Field Characterization of the GeoSTAR Demonstrator. IEEE Geoscience and Remote Sensing Symposium, 2529-2532.

[4] 孙延奎. 小波分析及其应用[M]. 北京: 机械工业出版社, 2005: 219-244.

[5] 刘丽, 江月松. 综合孔径成像原理与应用[M]. 北京: 国防工业出版社, 2013: 26-29, 117-120.

分享
Top