采用子孔径分割的逆合成孔径雷达成像包络对齐方法

Envelope Alignment Algorithm for Inverse Synthetic Aperture Radar Imaging Based on Splitting Sub-Apertures

针对低信噪比情况下难以对逆合成孔径雷达(ISAR)目标回波进行精确包络对齐的问题,提出了一种采用子孔径分割的逆合成孔径雷达成像包络对齐方法。该方法首先将全孔径划分为若干个相同长度的子孔径,并将每个子孔径的包络误差建模为线性,然后利用最小熵准则对子孔径包络误差进行估计,最后通过高阶多项式拟合实现对全孔径包络误差的精确估计。该方法具有更好的抗噪性和更高的估计精度,能对ISAR目标回波数据进行较为精确的包络误差补偿。仿真结果表明,在-5dB的低输入信噪比下,相对于传统方法,该方法成像结果的熵值降低了约0.6,说明取得了更好的包络对齐结果。

A novel envelope alignment algorithm based on splitting sub-apertures is proposed to improve the problem that it is hard for the envelope alignment to be accurately carried out under the condition of low signal to noise ratio （SNR） in inverse synthetic aperture radar （ISAR）. The full-aperture is divided into several sub-apertures with same length, and a linear model is built for envelope error of each sub-aperture. The minimum entropy criterion is used to estimate the envelope error of each sub-aperture. Then a high-order polynomial is used to fit the full-aperture envelope errors, and estimations of sub-apertures are used to successfully achieve the final envelope alignment precisely. Simulation results and comparisons with the traditional envelope alignment algorithms show that the proposed method has advantages in envelope alignment, and the entropy of imaging results reduces by about 0. 6 when the input SNR is as severe as -5 dB.