距离轮廓的相干平均

A. Zyweck, R. Bogner
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引用次数: 10

摘要

逆合成孔径雷达(ISAR)图像可用于雷达目标分类。为了在这些ISAR图像中获得合适的跨距离分辨率,需要目标和雷达之间的相对角度变化。在许多偶遇场景中,这种先决条件的方面更改是不可用的。在这些情况下,必须使用高分辨率距离像(HRRP)进行目标分类。本文提出了一种相干平均算法,该算法可以在给定雷达停留时间下提供最佳的可能HRRP。所得到的HRRP是用CFAR技术设定阈值的。将相干平均与非相干平均进行了比较,发现相干平均能提供更高的信噪比。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Coherent averaging of range profiles
Inverse synthetic aperture radar (ISAR) images can be used for radar target classification. To achieve a suitable cross-range resolution in these ISAR images, a relative aspect change is required between the target and the radar. In many encounter scenarios this prerequisite aspect change is not available. In these cases a high resolution range profile (HRRP) must be used for target classification. This paper presents a coherent averaging algorithm which provides the best possible HRRP for a given radar dwell time. The resultant HRRP is thresholded with a CFAR technique. Coherent averaging is compared with non-coherent averaging and coherent averaging is found to provide HRRPs with a higher SNR.
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