DATA EXTRAPOLATION FOR HIGH-RESOLUTION RADAR IMAGING

被引:47
|
作者
GUPTA, IJ
BEALS, MJ
MOGHADDAR, A
机构
[1] ElectroScience Laboratory, The Ohio State University, Columbus
基金
美国国家航空航天局;
关键词
D O I
10.1109/8.362783
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In radar imaging, AR modeling is sometimes used to extrapolate the scattered field data to obtain a high resolution image. In general, the Burg method is used to estimate the prediction parameters. The Burg method leads to a stable prediction biter but can also cause bias in the estimated spectra. One can also use the modified covariance method (MCM) to estimate the prediction parameters. These parameters lead to unbiased spectra. However, the MCM does not guarantee a stable prediction filter. One may have to modify the prediction parameters to ensure a stable prediction filter. One way to ensure stability is to reflect the unstable poles inside the unit circle. It is shown that the modified parameters can be used effectively for data extrapolation. The radar images obtained using this extrapolated data are more accurate than those obtained using the extrapolated data from the Burg prediction parameters.
引用
收藏
页码:1540 / 1545
页数:6
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