A Novel Method for Low-Speed Dim Small Target Detection

Fan Meng, Xue Ni, Guang Yang, Qianqian Jia
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引用次数: 1

Abstract

Low-speed dim small targets are not easily detected by radar in a clutter environment. In this paper, we propose a novel approach to improve the detection probability of low-speed dim small targets, which is to convert radar data into two-dimensional images to achieve background noise suppression. Firstly, we extract the data of the target and its surroundings by setting the detection domain and make the radar data map into the data of 256 gray grades for image processing. In order to suppress clutter, we develop the improved Bilateral filter (IBF) and apply the Doppler velocity as a weight term of the Gaussian function. Combined with the weight term of spatial distance, the detection domain can be significantly enhanced. Then, the target region contour is extracted by the adaptive threshold segmentation method from the background, and the target focused is accumulated, combining with Doppler velocity. The results show that the proposed method can effectively keep the edge of the target domain and weaken the noise background, thereby improving the detection probability of the target.
一种低速微弱目标检测新方法
在杂波环境下,低速弱小目标不易被雷达探测到。本文提出了一种提高低速弱小目标检测概率的新方法,即将雷达数据转换为二维图像,实现背景噪声的抑制。首先,通过设置检测域提取目标及其周围环境的数据,将雷达数据映射成256灰度级的数据进行图像处理。为了抑制杂波,我们开发了改进的双边滤波器(IBF),并将多普勒速度作为高斯函数的权项。结合空间距离权项,可以显著增强检测域。然后,采用自适应阈值分割方法从背景中提取目标区域轮廓,并结合多普勒速度对目标进行聚焦累加;结果表明,该方法能有效地保持目标域边缘,减弱背景噪声,从而提高目标的检测概率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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