西安电子科技大学学报

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一种时域降维多帧处理的Radon域弱目标检测

陈洪猛;李明;卢云龙;王泽玉;李刚飞;左磊;张鹏   

  1. (西安电子科技大学 雷达信号处理国家重点实验室,陕西 西安 710071)
  • 收稿日期:2016-04-11 出版日期:2017-04-20 发布日期:2017-05-26
  • 作者简介:陈洪猛(1986-),男,西安电子科技大学博士研究生,E-mail: chenhongmeng123@163.com
  • 基金资助:

    国家自然科学基金资助项目(61271297,61272281, 61301284);博士学科点科研专项基金资助项目(20110203110001);中国博士后基金资助项目(2014M562375)

Novel weak target detection technique based on time-dimension reduced multiple frame detection in the Radon domain

CHEN Hongmeng;LI Ming;LU Yunlong;WANG Zeyu;LI Gangfei;ZUO Lei;ZHANG Peng   

  1. (National Key Lab. of Radar Signal Processing, Xidian Univ., Xi'an 710071, China)
  • Received:2016-04-11 Online:2017-04-20 Published:2017-05-26

摘要:

对于低分辨率的警戒雷达,在强杂波背景下检测低空慢速小目标(“低、慢、小”)是一个具有挑战性的难题.该文提出一种基于时域降维多帧数据联合处理的Radon域“低、慢、小”目标检测新方法.该方法首先通过单帧数据的自适应杂波抑制和多帧数据的有序统计恒虚警滤波器处理,抑制掉部分强杂波;然后,对经过两级杂波抑制后的时间距离域数据进行时间维的降维和平滑;最后,对时间距离像进行Radon变换,将时间距离域的目标检测问题转化为Radon参数空间的特征提取问题,通过设置两级门限提取出微弱目标.由于时域降维处理在Radon域增大了目标相对于杂波的角度偏移量,因此,该方法不仅可检测到低速目标,还能估计出目标速度.实测数据处理结果验证了该方法的有效性.

关键词: 雷达, 弱目标检测, 多帧检测, Radon变换

Abstract:

Low-altitude slow-moving weak target detection in the heavy clutter is a challenging problem for low resolution radar. This paper proposes a time-dimension reduced multiple frame detection algorithm in the Radon domain to solve it. In our framework, adaptive moving target indication (AMTI) and the order statistic constant false alarm rate filter (OS-CFAR) are utilized to suppress the clutter primarily. After resampling and smoothing the combined time-range profiles in the time direction, the Radon transform is applied to this set of new time-range profiles. Then target detection is converted into a problem of feature extraction in the Radon domain, and the moving target can be figured out by two thresholds from the clutter in the parameter domain. Since the differences of skewing angles between the slow-moving targets and clutter in the Radon domain are amplified by time-dimension reduction operator, we can both detect the target and estimate its velocity. Real data demonstrate the effectiveness of the proposed algorithm.

Key words: radar, weak target detection, multiple frame detection, Radon transform

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