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An approach for interference detection and rejection from other sensors by using Hough Transform and image processing

机译:通过使用Hough变换和图像处理来从其他传感器中干扰检测和拒绝的方法

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This paper presents some results of studies on radar interference rejection using a Hough-Transform-based technique and image processing. If target detection is done by comparing the magnitude of each bin with a threshold produced by a CFAR algorithm, a number of radar systems operating at the same frequency band can cause reciprocal interference, thereby affecting detection and increasing false alarm probability. In this work we will refer to this interference as to “other sensor interference” (OSI). The goal of this work is the definition of methods to detect and remove the interference patterns from radar raw video images. We show that the substitution of interferences with samples estimated from cells (cross range samples) in close proximity of the OSI-affected samples allows CFAR algorithms performance to be improved.
机译:本文介绍了使用基于霍夫变换的技术和图像处理的雷达干扰抑制研究的一些结果。如果通过将每个垃圾箱的大小与由CFAR算法产生的阈值进行比较来完成目标检测,则在相同频带处操作的许多雷达系统会导致互易干扰,从而影响检测并增加误报概率。在这项工作中,我们将参考“其他传感器干扰”(OSI)的干扰。这项工作的目标是检测和去除来自雷达原始视频图像的干扰模式的方法的定义。我们表明,替代来自细胞(交叉范围样本)估计的样品在osi影响的样本附近估计,允许改善CFAR算法性能。

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