基于遗传算法的超视距雷达机动目标检测

Dai Wenjuan, Huang Jingfeng, Xu Dingwen, Wang Zixi
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引用次数: 1

摘要

在其他系统中,用于运动目标检测的信杂比(SCR)非常低。飞机、导弹等多普勒频率机动目标具有时变、扩散性和积分时间长的特点。在这种情况下,基于傅里叶变换的目标检测和跟踪技术可能无法很好地处理长CIT,因为在CIT长度和多普勒分辨率之间存在权衡。本文提出了一种新的机动弱目标检测方法。首先利用时频分布技术估计目标参数的范围,然后利用遗传算法对目标参数进行精确估计。时频分布的意义在于缩小遗传算法的搜索范围,提高遗传算法的处理效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Maneuvering target detection in over-the-horizon radar based on genetic algorithm
In OTHR systems, the signal-to-clutter ratio (SCR) used for moving targets detection is very low. The Doppler frequency maneuvering targets, such as aircraft and missiles, is time-varying and spreading with long integration time (CIT). In this situation, the Fourier transform based target detection and tracking techniques may fail to work well with a long CIT, because there is a trade-off between the CIT length and Doppler resolution. A new method to detect maneuvering weak targets in the OTHR systems is proposed here. Time-frequency distribution techniques have been used to estimate the range of parameters of targets firstly, then, genetic algorithm (GA) is used to estimate the parameters accurately. The significance of time-frequency distribution is to narrow the search range of GA, and this operation can improve the processing efficiency.
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