海杂波环境下的弱小目标检测方法研究
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摘要
海杂波环境下低RCS的弱小目标检测在军事领域以及民用领域都有着重要的应用价值，由于海杂波的似目标特性以及弱小目标的低信杂比（SCR）导致虚警概率较高，目标在杂波区不能有效被检测到。传统的海杂波背景下目标检测算法是根据海杂波的幅度统计模型而制定的检测策略。但是随着现代雷达距离分辨率的不断提高，在高分辨低擦地角的情况下海杂波回波的幅度模型逐渐偏离了传统的幅度统计模型，因此导致传统检测器的性能急剧下降，而新发现的海杂波模型也受到很多条件的限制，适应范围比较窄。因此寻求新的海杂波背景下弱小目标检测算法就成为了一个研究热点。本文针对这一问题展开了相关检测算法的研究工作，论文的主要工作如下：
1．首先分析了海杂波的形成机理以及海面的构成，阐明了海杂波的主要构成是由重力波和由风引起的风波以及表面张力引起的毛细波构成的。文中总结分析了海杂波分布模型并对IPIX雷达实测数据进行了幅度统计分析与拟合，分别与常用的海杂波幅度统计分布模型进行了拟合对比，并对拟合结果进行了检验。得出了在该组海杂波数据中K分布的拟合效果最好。
2．从K个独立同分布的二级数据的联合概率密度函数推导了固定点协方差矩阵，构造了使用Toeplize矩阵为初始矩阵的T-FP法。在实测非高斯海杂波环境下对该方法进行了检测性能仿真与分析，仿真结果表明与常用的几种杂波协方差矩阵构造相比T-FP法在信杂比较小的情况下可以获得较好的检测效果。
3．针对弱小目标在高分辨雷达下的跨距离单元和较低SCR不利于检测的问题，提出了一种基于Radon变换的强海杂波下雷达高速弱小目标检测算法。该算法通过对高分辨雷达回波数据进行Radon变换，将时间—距离域数据变换到参数域，此过程中将目标呈现出来的线状特征变换成峰值强度，在参数域对杂波和信号的峰值进行处理，最后在能量与角度域对目标进行检测。由于在变换和处理过程中对杂波进行了抑制处理，对信号进行了长时间的能量累积且不受目标跨距离单元的影响，因此可以在较低的信杂比条件下检测到弱小目标。接着在Radon变换的基础上提出了基于Radon逆变换的海杂波中弱小目标检测算法，经过杂波抑制与目标信号累积后将检测到的弱小目标逆变换回时间-距离域，由于在参数域的处理提高了信杂比，因此变换回时间-距离域后可以得到弱小目标的航迹信息。
4．针对海杂波环境下弱小目标信杂比较低的问题，提出了一种多重分形谱的均方和测试量来检测海杂波中的弱小目标。分析了真实海杂波数据的多重分形特征，研究了无目标的纯海杂波与混有目标的海杂波之间的差异。通过对实测海杂波数据的重新截取构造了新的不同信杂比（SCR）的海杂波序列，使用新构造的数据对算法进行分析验证，并分析了海杂波的分形特征，包括目标与杂波之间的关系，盒维数与SCR之间的关系，均方和测试量与SCR之间的关系，以及每个测试中分形特征与序列长度变化之间的关系。分析结果显示了该检测算法可以在较低SCR下有效检测出目标。
The sea clutter low RCS weak target detection in the field of military and civilianareas has important applications, lead to a higher probability of false alarm due to thesea clutter like the target characteristic as well as the weak target in low signal-to-noiseratio (SCR),The target can not effectively be detected in the clutter area. Traditional seaclutter in the context of target detection algorithm is developed based on the magnitudeof the sea clutter statistical model detection strategy. However, with the continuousimprovement of modern radar range resolution, in the case of low grazing angle seaclutter returns average RCS reduced, sea clutter echo amplitude model graduallydeviated from the Gaussian statistical model, thus leading to the sharp decline inperformance of the conventional detector. Newly discovered sea clutter model is limitedby many conditions, to adapt to the relatively narrow scope, so seek new Sea Cluttersmall target detection algorithm has become a hot research topic. In this thesis, novel seaclutter low RCS target detection methods are studied. The main contributions of thisthesis are as follows:
1.First, the formation mechanism of sea clutter is analyzed as well as thecomposition of the sea, to clarify the main components of sea clutter is constituted bythe gravity waves caused by the wind storm and surface tension induced capillary waves.Sea clutter distribution model is analyzed and the the IPIX radar measured data of theamplitude is statistical analysised and fitting, fitting contrast with the commonly usedstatistical distribution model of sea clutter amplitude, and fitting results have been tested.Simulation results demonstrate the best fit K distribution model in this group of seaclutter data.
2．K independent and identically distributed joint probability density function of thesecondary data derived fixed-point covariance matrix for the initial matrix use Toeplizematrix T-FP method. The method was measured in non-Gaussian clutter to test thedetection performance. Simulation results show that compared with several commonlyused clutter covariance matrix structure, T-FP method in the case of relatively smallsignal-to-clutter can be obtained better detection results.
3.High-speed small target detection algorithm based on Radon transform in strongsea clutter environment is proposed, the algorithm take Radon transform onhigh-resolution radar echo data into parameter field. In parameter field the targetpresented linear characteristics is converted into a peak intensity, threshold and theclustering process is then carried out for each peak, to detect the target in energy and angle domain, the energy accumulated in the transformation process, the sea clutter issuppressed, target can be detected in low SCR conditions. Then on the basis of theRadon transform, the Radon inversion transform weak target detection algorithm isproposed, the methods can suppress the clutter, the target can be transformed back to thetime-range domain, the weak target track information can be clearly detected.
4.Multi-fractal characteristics of the real sea clutter data are analyzed. Weresearched the difference between the no-target pure sea clutter with sea clutter mixedtarget in. Proposed a mean square test methods based multi-fractal characteristic oftarget. Construct the new sea clutter data series with different SCR to test the proposedmethod performance. The thesis analyzed the fractal characteristics of the sea clutterand relationship of target and sea clutter, also analyzed the relationship of boxdimension and SCR, relationship of mean square test and SCR. Simulation results showthe algorithm can detect the targets in low RCS.
1．首先分析了海杂波的形成机理以及海面的构成，阐明了海杂波的主要构成是由重力波和由风引起的风波以及表面张力引起的毛细波构成的。文中总结分析了海杂波分布模型并对IPIX雷达实测数据进行了幅度统计分析与拟合，分别与常用的海杂波幅度统计分布模型进行了拟合对比，并对拟合结果进行了检验。得出了在该组海杂波数据中K分布的拟合效果最好。
2．从K个独立同分布的二级数据的联合概率密度函数推导了固定点协方差矩阵，构造了使用Toeplize矩阵为初始矩阵的T-FP法。在实测非高斯海杂波环境下对该方法进行了检测性能仿真与分析，仿真结果表明与常用的几种杂波协方差矩阵构造相比T-FP法在信杂比较小的情况下可以获得较好的检测效果。
3．针对弱小目标在高分辨雷达下的跨距离单元和较低SCR不利于检测的问题，提出了一种基于Radon变换的强海杂波下雷达高速弱小目标检测算法。该算法通过对高分辨雷达回波数据进行Radon变换，将时间—距离域数据变换到参数域，此过程中将目标呈现出来的线状特征变换成峰值强度，在参数域对杂波和信号的峰值进行处理，最后在能量与角度域对目标进行检测。由于在变换和处理过程中对杂波进行了抑制处理，对信号进行了长时间的能量累积且不受目标跨距离单元的影响，因此可以在较低的信杂比条件下检测到弱小目标。接着在Radon变换的基础上提出了基于Radon逆变换的海杂波中弱小目标检测算法，经过杂波抑制与目标信号累积后将检测到的弱小目标逆变换回时间-距离域，由于在参数域的处理提高了信杂比，因此变换回时间-距离域后可以得到弱小目标的航迹信息。
4．针对海杂波环境下弱小目标信杂比较低的问题，提出了一种多重分形谱的均方和测试量来检测海杂波中的弱小目标。分析了真实海杂波数据的多重分形特征，研究了无目标的纯海杂波与混有目标的海杂波之间的差异。通过对实测海杂波数据的重新截取构造了新的不同信杂比（SCR）的海杂波序列，使用新构造的数据对算法进行分析验证，并分析了海杂波的分形特征，包括目标与杂波之间的关系，盒维数与SCR之间的关系，均方和测试量与SCR之间的关系，以及每个测试中分形特征与序列长度变化之间的关系。分析结果显示了该检测算法可以在较低SCR下有效检测出目标。
The sea clutter low RCS weak target detection in the field of military and civilianareas has important applications, lead to a higher probability of false alarm due to thesea clutter like the target characteristic as well as the weak target in low signal-to-noiseratio (SCR),The target can not effectively be detected in the clutter area. Traditional seaclutter in the context of target detection algorithm is developed based on the magnitudeof the sea clutter statistical model detection strategy. However, with the continuousimprovement of modern radar range resolution, in the case of low grazing angle seaclutter returns average RCS reduced, sea clutter echo amplitude model graduallydeviated from the Gaussian statistical model, thus leading to the sharp decline inperformance of the conventional detector. Newly discovered sea clutter model is limitedby many conditions, to adapt to the relatively narrow scope, so seek new Sea Cluttersmall target detection algorithm has become a hot research topic. In this thesis, novel seaclutter low RCS target detection methods are studied. The main contributions of thisthesis are as follows:
1.First, the formation mechanism of sea clutter is analyzed as well as thecomposition of the sea, to clarify the main components of sea clutter is constituted bythe gravity waves caused by the wind storm and surface tension induced capillary waves.Sea clutter distribution model is analyzed and the the IPIX radar measured data of theamplitude is statistical analysised and fitting, fitting contrast with the commonly usedstatistical distribution model of sea clutter amplitude, and fitting results have been tested.Simulation results demonstrate the best fit K distribution model in this group of seaclutter data.
2．K independent and identically distributed joint probability density function of thesecondary data derived fixed-point covariance matrix for the initial matrix use Toeplizematrix T-FP method. The method was measured in non-Gaussian clutter to test thedetection performance. Simulation results show that compared with several commonlyused clutter covariance matrix structure, T-FP method in the case of relatively smallsignal-to-clutter can be obtained better detection results.
3.High-speed small target detection algorithm based on Radon transform in strongsea clutter environment is proposed, the algorithm take Radon transform onhigh-resolution radar echo data into parameter field. In parameter field the targetpresented linear characteristics is converted into a peak intensity, threshold and theclustering process is then carried out for each peak, to detect the target in energy and angle domain, the energy accumulated in the transformation process, the sea clutter issuppressed, target can be detected in low SCR conditions. Then on the basis of theRadon transform, the Radon inversion transform weak target detection algorithm isproposed, the methods can suppress the clutter, the target can be transformed back to thetime-range domain, the weak target track information can be clearly detected.
4.Multi-fractal characteristics of the real sea clutter data are analyzed. Weresearched the difference between the no-target pure sea clutter with sea clutter mixedtarget in. Proposed a mean square test methods based multi-fractal characteristic oftarget. Construct the new sea clutter data series with different SCR to test the proposedmethod performance. The thesis analyzed the fractal characteristics of the sea clutterand relationship of target and sea clutter, also analyzed the relationship of boxdimension and SCR, relationship of mean square test and SCR. Simulation results showthe algorithm can detect the targets in low RCS.
引文
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