海上船只目标多角度成像技术
发布时间：2018-12-24 10:12
【摘要】：将斜视滑动聚束合成孔径雷达(SAR)应用于海上船只目标的成像。利用斜视角的变化,斜视滑动聚束SAR可高频次地得到同一船只在不同斜视角下的多幅高分辨率微波图像,有利于船只目标的分类与识别。将斜视滑动聚束SAR高效成像算法与船只目标逆合成孔径雷达(ISAR)重聚焦算法相结合,针对计算机仿真数据开展了成像处理实验,取得了较好的成像效果,验证了斜视滑动聚束SAR应用于船只目标成像时可高频次地获得多幅高分辨率图像的独特优势。
[Abstract]:The strabismus Spotlight synthetic Aperture Radar (SAR) is applied to the imaging of ship targets at sea. Based on the variation of squint angle, multiple high-resolution microwave images of the same ship with different oblique angles can be obtained by strabismus sliding spotlight SAR at high frequency, which is beneficial to the classification and recognition of ship targets. The high efficiency imaging algorithm of squint sliding spotlight SAR is combined with the (ISAR) refocusing algorithm of ship target inverse synthetic aperture radar (SAR). The imaging processing experiments are carried out against the computer simulation data, and good imaging results are obtained. The advantages of multiple high-resolution images can be obtained at high frequency when strabismus gliding spotlight SAR is applied to ship target imaging.
【作者单位】： 中国石油大学(华东)信息与控制工程学院;
【基金】：海洋公益性科研专项(201505002) 国家自然科学基金项目(61501520)资助~~
【分类号】：TN957.52
，
本文编号：2390496
[Abstract]:The strabismus Spotlight synthetic Aperture Radar (SAR) is applied to the imaging of ship targets at sea. Based on the variation of squint angle, multiple high-resolution microwave images of the same ship with different oblique angles can be obtained by strabismus sliding spotlight SAR at high frequency, which is beneficial to the classification and recognition of ship targets. The high efficiency imaging algorithm of squint sliding spotlight SAR is combined with the (ISAR) refocusing algorithm of ship target inverse synthetic aperture radar (SAR). The imaging processing experiments are carried out against the computer simulation data, and good imaging results are obtained. The advantages of multiple high-resolution images can be obtained at high frequency when strabismus gliding spotlight SAR is applied to ship target imaging.
【作者单位】： 中国石油大学(华东)信息与控制工程学院;
【基金】：海洋公益性科研专项(201505002) 国家自然科学基金项目(61501520)资助~~
【分类号】：TN957.52
，
本文编号：2390496
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