现代防御技术 ›› 2022, Vol. 50 ›› Issue (2): 67-75.DOI: 10.3969/j.issn.1009-086x.2022.02.010

• 目标特性与探测跟踪技术 • 上一篇    下一篇

基于时间反转变换的动目标相参积累算法

刘海涵, 吕卫祥   

  1. 南京船舶雷达研究所724所,江苏 南京 211106
  • 收稿日期:2021-08-01 修回日期:2021-09-13 出版日期:2022-04-28 发布日期:2022-04-29
  • 作者简介:刘海涵(1996-),男,江苏徐州人。硕士生,研究方向为雷达目标检测技术。通信地址:211106 江苏省南京市长青街 32 号鹏力宿舍楼 E-mail:120666990@qq.com

A Phase Coherent Accumulation Algorithm of Moving Target Based on Time Reversal Transformation

Hai-han LIU, LU¨ Wei-xiang   

  1. Nanjing Marine Radar Research Institute 724,Jiangsu Nanjing 211106,China
  • Received:2021-08-01 Revised:2021-09-13 Online:2022-04-28 Published:2022-04-29

摘要:

高速动目标回波能量的相参积累一直是国内外学者的研究热点。针对时间反转变换-二阶Keystone变换-吕分布(TRT-SKT-LVD)算法在积累过程中丢失速度信息的问题,提出时间反转变换-一阶Keystone变换-Radon变换(TRT-KTR)算法实现动目标速度的分离与相参积累。通过时间反转分离出目标的速度信息,采用低通滤波器和线性平滑法消除噪声引起的突变点的影响。用一阶Keystone变换校正目标速度引起的距离走动。利用Radon变换估计速度模糊数并进行补偿实现相参积累。仿真证明,该算法可以有效分离并积累目标的速度分量,且拥有较低的运算量。结合TRT-SKT-LVD后的联合算法可积累出目标距离、速度、加速度三维信息,实现多目标检测。

关键词: 目标检测, 相参积累, 时间反转变换, Keystone变换, Radon变换

Abstract:

The coherent accumulation of echo signals of high-speed moving targets has always been a research hotspot for domestic and foreign scholars. Aiming at the problem that the time reversing transform, the second-order Keystone transform and LV’s distribution (TRT-SKT-LVD) algorithm loses velocity information in the process of accumulation, a time reversing transform, the first-order Keystone transform and Radon transform (TRT-KTR) algorithm is proposed to achieve velocity separation and phase-coherent accumulation of moving targets. The velocity information of the target is separated by time reversal and the impact of the abrupt point caused by noise is eliminated by low pass filter and linear smoothing method. The first order Keystone transform is used to correct the range migration caused by the target velocity. The Radon transform is used to estimate the fuzzy number of velocity and compensate to realize phase-coherent accumulation. Simulation results show that the algorithm can effectively separate and accumulate the velocity components of the target, and has a low computational cost. Combined with TRT-SKT-LVD, the joint algorithm can accumulate 3D information of target distance, speed and acceleration, and realize multi-target detection.

Key words: target detection, phase-coherent accumulation, time reversing transform, Keystone transform, Radon transform

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