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HF Radar Signal Processing Based on Tomographic Imaging and CS Technique

机译:基于层析成像和CS技术的HF雷达信号处理

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This study presents the application of a spotlight-mode synthetic aperture radar (SAR) imaging technique to the problem of high probablity target detection in high frequency (HF) radar system, attempting to improve its spatial resolution. The effects of finite aperture on resolution, sampling constraints and reconstruction over a complete angular range of 360 degrees are discussed. A Convolution Back Projection (CBP) algorithm has been applied to image reconstruction. In order to solve the range limitation of aspect angle with one radar-carrying platform, we collect data over a larger azimuthal range by making multi-aspect observations. Each straight line is a sub aperture over which we can perform the CBP algorithm. When we demand higher resolution for stationary target, it will cause blur with longer data acquisition time. Thus the application of the traditional imaging algorithm is limited. Compressed Sensing (CS) has recently attracted much interest as it can reduce the number of samples without compromising the imaging quality. Within this motivation, we discuss the applicability of CS and present the application constraint for HF radar system.
机译:这项研究提出了聚光模式合成孔径雷达(SAR)成像技术在高频(HF)雷达系统中的高概率目标检测问题中的应用,试图提高其空间分辨率。讨论了有限孔径对分辨率,采样约束和整个360度角范围内的重构的影响。卷积反投影(CBP)算法已应用于图像重建。为了解决使用一个雷达承载平台的纵横角范围限制的问题,我们通过进行多角度观测来收集更大方位角范围内的数据。每条直线都是一个子孔径,我们可以在其上执行CBP算法。当我们对固定目标要求更高的分辨率时,它将导致模糊,并延长数据采集时间。因此,传统成像算法的应用受到限制。压缩感测(CS)最近吸引了很多关注,因为它可以减少样本数量而不影响成像质量。在此动机下,我们讨论了CS的适用性,并提出了HF雷达系统的应用约束。

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