A new iterative algorithm for extrapolation of data available in multiple restricted regions with application to radar imaging
A new iterative algorithm for extrapolation of data available in multiple restricted regions with application to radar imaging
复制标题
DOI：
10.1109/tap.1987.1144138
复制
发表时间：
1987-05
影响因子：
5.7
通讯作者：
Hsueh-Jyh Li;N. Farhat;Yuhsyen Shen
中科院分区：
文献类型：
--
作者：
Hsueh-Jyh Li;N. Farhat;Yuhsyen Shen
提出并测试了一种新的迭代方法，用于推断多个分离带中可用的不完整分段数据。该方法使用burg算法来找到线性预测参数和迭代过程，以改善线性预测参数的估计和数据外推。当在此处表示的雷达成像的背景下，当光谱（观察到的数据的傅立叶变换）以离散形式（观察到的数据的傅立叶变换）时，此方法特别有效，这意味着对象由明显的间隔散射中心组成。使用与高分辨率雷达成像有关的数值生成和现实的实验数据证明了该算法的优势。
A new iterative method for extrapolation of incomplete segmented data available in multiple separated bands is proposed and tested. The method uses the Burg algorithm to find the linear prediction parameters and an iterative procedure to improve the estimation of the linear prediction parameters and the extrapolation of the data. This method is especially effective when the spectra (Fourier transform of the observed data) are in discrete forms, in the context of radar imaging represented here, this means the objects consist of distinctly spaced scattering centers. The advantages of this algorithm are demonstrated using both numerically generated and realistic experimental data pertaining to high resolution radar imaging.