基于HHT的星载SAR海面动目标检测
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摘要
为了提高星载SAR海面动目标检测及参数估计的准确性,针对强杂波场景下的目标回波信号被海杂波及噪声淹没的问题,提出了一种基于经验模态分解(Empirical Mode Decomposition,EMD)阈值滤波及Hilbert-Huang变换(Hilbert-Huang transform,HHT)的海面动目标检测及参数估计算法。算法首先通过EMD将回波分解为杂波和目标分量等,通过EMD阈值滤波滤除大部分海杂波和噪声,然后计算目标分量的瞬时频率,获得频率随时间变化的HHT谱,最终利用线性拟合估计目标运动参数。算法自适应对信号进行分解,去噪和抑制杂波操作简单,并可同时对多目标进行运动参数估计,有助于简化多目标运动检测和参数估计流程。仿真结果表明了算法的有效性。
In order to improve the accuracy of the detection and parameter estimation of moving targets in the space-borne SAR, aiming at the problem that target echo signals are submerged in sea clutter and noises in the strong clutter scenario, an algorithm based on EMD threshold filtering and the Hilbert-Huang Transform(HHT) is given in this paper. Firstly, empirical mode decomposition(EMD) was used to decompose echoes into clutter and target components. Most of the clutter and noise was filtered out by EMD threshold filtering. Then the instantaneous frequency of the target component wass calculated to obtain the HHT spectrum with time-varying. Finally, target motion parameters w estimated by using linear fit. The algorithm adaptively decomposes the signal, denoising and suppressing clutter are easy to operate, and it can simultaneously estimate the motion parameters of multiple targets, which helps to simplify the multi-target motion detection and parameter estimation flow. Simulation results show the validity of the algorithm.
In order to improve the accuracy of the detection and parameter estimation of moving targets in the space-borne SAR, aiming at the problem that target echo signals are submerged in sea clutter and noises in the strong clutter scenario, an algorithm based on EMD threshold filtering and the Hilbert-Huang Transform(HHT) is given in this paper. Firstly, empirical mode decomposition(EMD) was used to decompose echoes into clutter and target components. Most of the clutter and noise was filtered out by EMD threshold filtering. Then the instantaneous frequency of the target component wass calculated to obtain the HHT spectrum with time-varying. Finally, target motion parameters w estimated by using linear fit. The algorithm adaptively decomposes the signal, denoising and suppressing clutter are easy to operate, and it can simultaneously estimate the motion parameters of multiple targets, which helps to simplify the multi-target motion detection and parameter estimation flow. Simulation results show the validity of the algorithm.
引文
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[2] 易航,黄晓涛,李杨寰.一种单通道SAR对多个地面动目标定位的方法[J].计算机仿真,2010,27(06):6-9+30.
[3] X Lv,et al.Keystone transformation of the Wigner-Ville distribution for analysis of multicomponent LFM signals[J].Signal Processing,2009,89(5):791-806.
[4] 黄勇,等.基于短时分数阶傅里叶变换的海面微动目标检测和特征提取方法[P].CN 102788969 B,2015.
[5] 姜恒.时频分析在雷达信号参数估计中的应用研究[D].南京航空航天大学,2011.
[6] 陈小龙,等.海杂波背景下基于FRFT的多运动目标检测快速算法[J].信号处理,2010,26(8):1174-1180.
[7] 许学明.改进的希尔伯特—黄变换及其在信号时频分析中的应用[D].南京信息工程大学,2012.
[8] 吴桂生,田振,察豪.希尔伯特-黄变换在SAR信号处理中的应用研究[J].雷达与对抗,2011,31(4):16-20.
[9] 李光辉.基于希尔伯特黄变换及其改进方法的信号分析研究与应用[D].成都理工大学,2012.
[10] 张晓楠.EMD算法的改进及其在非平稳信号处理中的应用[D].郑州大学,2014.
[11] 陈华丽,刘康,程耕国.信号自适应去噪方法的仿真研究[J].计算机仿真,2011,28(1):344-347,387.
[12] 李雪,等.基于已知传播模式数目的海杂波抑制方法研究[J].电波科学学报,2016,31(4).
[13] 田振,周沫,肖春生.基于希尔伯特-黄变换的海杂波特性分析[J].火力与指挥控制,2012,37(10):93-95.
[14] 朱丽平,等.基于HHT的雷达杂波抑制[J].现代防御技术,2011,39(6):185-190.
[15] M Cao,et al.High resolution range profile imaging of high speed moving targets based on fractional Fourier transform[C].International Symposium on Multispectral Image Processing and Pattern Recognition.International Society for Optics and Photonics,2007:259-270.