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Multi-Targets Miss Distance Measurement based on a Sequence of Image Processing Techniques

机译:基于一系列图像处理技术的多目标脱靶距离测量

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Multi-targets miss distance measurement is studied in this paper based on a sequence of image processing techniques. Firstly, echoes from multi-targets are represented as a gray image with spectral intensity as its gray values by time-frequency transform. Then an adaptive threshold based on constant false alarm rate (CFAR) detection is devised to convert the gray image into a binary image. Further, a set of morphological operations is used to remove background noise from the binary image. Finally, miss distance parameters of multi-targets are obtained based on randomized Hough transform (RHT). The experimental results show the efficiency of proposed method.
机译:基于一系列图像处理技术,研究了多目标错过距离测量。首先,通过时频变换将来自多目标的回波表示为光谱强度为灰度值的灰度图像。然后,设计了基于恒定虚警率(CFAR)检测的自适应阈值,将灰度图像转换为二进制图像。此外,一组形态学运算用于从二进制图像中去除背景噪声。最后,基于随机霍夫变换(RHT)获得了多目标的脱靶距离参数。实验结果表明了该方法的有效性。

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