西安电子科技大学学报 ›› 2023, Vol. 50 ›› Issue (2): 188-196.doi: 10.19665/j.issn1001-2400.2023.02.019

• 网络空间安全与其他 • 上一篇    下一篇

改进奇异值分解的海杂波抑制算法

国强1,2(),陈佳甜2,3(),戚连刚1,2(),CHORNOGOR Leonid4()   

  1. 1.哈尔滨工程大学 信息与通信工程学院,黑龙江 哈尔滨 150001
    2.哈尔滨工程大学 先进船舶通信与信息技术工业和信息化部重点实验室,黑龙江 哈尔滨 150001
    3.哈尔滨工程大学 物理与光电工程学院,黑龙江 哈尔滨 150001
    4.乌克兰哈尔科夫国立大学 空间无线电物理系,乌克兰 哈尔科夫 61022
  • 收稿日期:2022-05-11 出版日期:2023-04-20 发布日期:2023-05-12
  • 作者简介:国 强(1972—),男,教授,E-mail:guoqiang@hrbeu.edu.cn;|陈佳甜(1999—),女,哈尔滨工程大学硕士研究生,E-mail:cjt@hrbeu.edu.cn;|戚连刚(1990—),男,讲师,E-mail:qiliangang@hrbeu.edu.cn;|CHORNOGOR Leonid(1950—),男,教授,E-mail:leonid.f.chernogor@gmail.com
  • 基金资助:
    国家重点研发计划(2018YFE0206500);国家自然科学基金面上项目(62071140);自由探索项目(3072022CF0801)

Sea clutter suppression algorithm based on improved singular value decomposition

GUO Qiang1,2(),CHEN Jiatian2,3(),QI Liangang1,2(),CHORNOGOR Leonid4()   

  1. 1. College of Information and Communication Engineering,Harbin Engineering University,Harbin 150001,China
    2. Key Laboratory of Advanced Marine Communication and Information Technology,Ministry of Industry and Information Technology,Harbin Engineering University,Harbin,150001,China
    3. College of Physics and Optoelectronic Engineering,Harbin Engineering University,Harbin 150001,China
    4. Department of Space Radiophysics,Kharkov State University of Ukraine,Kharkov 61022,Ukraine
  • Received:2022-05-11 Online:2023-04-20 Published:2023-05-12

摘要:

针对强海杂波背景下海面运动目标回波信号难以检测的问题,提出了一种奇异值分解和双延迟线对消算法相结合的海杂波抑制算法。首先将脉冲压缩后的目标回波信号按周期重排成快慢时间维度矩阵,进行周期奇异值分解;然后构造出信号所对应奇异值的阈值和输入信杂噪比的关系,利用阈值对奇异值指数比进行判决,实现自适应区分海杂波和目标信号;最后对重构后的目标信号进行双延迟线对消,抑制杂波的同时确保目标信号的损失降到最低。采用实测数据对算法性能进行实验验证,相比于现有的海杂波抑制算法,所提方法能够适应目标回波序列信杂噪比的变化,在输入信杂噪比为-30 dB下仍能抑制大部分杂波并准确检测信号,由此验证了新算法具有更好的抑制效果和更优的检测性能。

关键词: 目标检测, 海杂波, 杂波抑制, 奇异值分解, 双延迟线对消算法

Abstract:

Aiming at the problem that the echo signals of moving targets on the sea surface are difficult to detect in the background of a strong sea clutter,a sea clutter suppression algorithm (SVD-MTI algorithm for short) is proposed,which combines singular value decomposition (SVD) and dual delay line pair elimination algorithm.First,the pulse-compressed target echo signals are periodically rearranged into a matrix of fast and slow time dimensions,and the periodic singular value decomposition is performed;Then,it is proposed that the threshold value of the singular value corresponding to the signal and the input signal to clutter plus noise ratio obey Gaussian distribution,and that the threshold value is used to judge the energy singular value exponential ratio,so as to realize the adaptive distinction between sea clutter and target signal.Finally,dual delay line pair elimination is performed on the reconstructed target signal to suppress the clutter and minimize the loss of the target signal.The performance of the algorithm is experimentally verified by using the measured data.Compared with the existing sea clutter suppression algorithm,the proposed method can adapt to the change of the signal to clutter plus noise ratio of the target echo sequence,and can still suppress most of the clutter when the input SCNR is -30dB,and accurately detect the signal,which verifies that the new algorithm has a better suppression effect and a better detection performance.

Key words: target detection, sea clutter, clutter suppression, singular value decomposition, dual delay line pair elimination algorithm

中图分类号: 

  • TN957.51
Baidu
map