高海况条件下海面漂浮小目标特征提取与分析

在高海况条件下,海面小目标回波信杂比很低,且在海浪影响下,小目标姿态变化引起的能量起伏严重,以能量为主导的目标检测方法具有较大的性能损失。从不同表示域提取小目标与海杂波差异特征,并进行特征检测是解决该问题的有效途径。以此为背景,通过开展海面小目标数据采集试验,分别从时域、频域、时频域、时频脊变换域进行特征提取与可分性分析,在 4个表示域共提取出 10个特征,包括时域相对平均幅度(RelativeAverageAm-plitude,RAA)、频域相对多普勒向量熵(RelativeVectorEntropy,RVE)、时频脊累积量(RidgeIntegration,RI)等,通过分析得到了 4级海况条件下不同特征可分性程度的结论,为后续多特征融合以及多维特征目标检测工作提供支撑。     

基于实测数据的海杂波时空相关性分析

海杂波的相关特性分为时间相关性和空间相关性,二者均与雷达系统参数、环境条件等多种因素有关。文章利用X波段雷达实测海杂波数据,重点研究了不同极化条件下海杂波的时间相关性、高低典型海况和不同入射余角条件下的海杂波距离向和方位向空间相关性。经大量实测数据验证表明,极化方式对海杂波强时间相关性影响较小,海杂波距离向空间相关性受海况影响较大、方位向相邻分辨单元空间相关性较弱,这些结论对于海杂波中目标检测方法优化设计具有重要意义。     

海杂波谱的机理及时变特性分析

针对海杂波背景下目标检测问题的实际需求,在机理分析的基础上,利用实测数据对海杂波谱的时变特性进行了分析。首先,分析了波束照射区域内由海表面波浪运动引起的多普勒频移和展宽现象,以及随雷达工作参数之间的依赖关系;然后,对已有海杂波谱机理研究结果进行了分析和总结。在此基础上,利用加窗的周期图法估计得到海杂波的时间-多普勒谱,进而从相关时间的统计特性、谱宽与时域海杂波拖尾程度的依赖关系两个层面对海杂波谱的时变特性进行了分析。分析结果可为海杂波谱建模、海杂波抑制及目标检测方法设计提供理论指导。     

无线电引信抗海杂波干扰方法

无线电引信抗海杂波的能力决定了舰空导弹无线电引信低空和超低空工作性能,针对海杂波对无线电引信的影响,分析了海面回波的平均功率、海面散射系数、海杂波的多普勒频谱等海杂波特性,提出了无线电引信抗海杂波干扰方法。     

海杂波FRFT域分形特征在动目标检测中的应用

文中研究了海上动目标雷达回波与海杂波在分数阶Fourier域(FRFT域)的分形特性,利用两者幅值起伏程度的不同,提出了一种基于FRFT域分形维数差异的动目标检测方法。该方法以处处连续而不可导的非平稳不规则信号模型——分数布朗运动作为FRFT域分形模型,通过仿真分析实测海杂波数据的分形曲线,证明海杂波在FRFT域的无标度区间内具有分形特性。提取出FRFT域海杂波与动目标回波的分形维数,并利用其固有的差异进行目标检测。经不同极化方式下海杂波数据仿真,验证了算法的有效性。     

海上舰船目标的宽带雷达散射特征信号仿真

提出一种将目标高频电磁（EM）散射计算多径回波模型与不同海况条件下粗糙海面前向复反射系数模型相结合的方法,对海上舰船目标宽带雷达回波进行仿真和分析。简要分析了目标-海面相互作用的多径回波模型,给出了目标体的电磁散射计算方法,研究了不同海况条件下海面前向复反射系数随频率和擦地角的变化特性,并通过仿真分析了海面对舰船目标雷达回波的影响。对比分析舰船目标体直接散射及在不同海况条件下考虑多径效应时的雷达散射截面（RCS）变化特性,并在不同海况条件下对目标进行二维逆合成孔径雷达（ISAR）成像仿真,验证了本文方法的有效性。     

信息动态

【项目编号】2007ZC07003【项目负责人】邱朝阳【依托单位】中国航空工业雷达与电子设备研究院海杂波背景下小目标检测技术研究完成情况简介:本项目在开展专题技术调研、资料搜集与整理的基础上,完成了海杂波特性分析的研究;基于研究所得的海杂波的混沌特性,开展了小目标检测算法的研究;对检测前跟     

大入射余角海杂波相关特性分析及幅度拟合

对入射余角44°到74°的海杂波实测数据进行时间相关性、空间相关性分析,并提出了一种新的海杂波幅度拟合混合分布。实验表明,海杂波相关时间维持在毫秒量级,且随着入射余角增加,先增加后减小,时间相关性最强的入射余角在60°左右,而平均相关距离单元个数一直增加。通过KK分布、Rayleigh分布与K分布的对比,表明新的混合分布对大入射余角海杂波的拖尾特性具有良好的拟合效果。     

利用神经网络的海杂波幅度分布参数估计方法

海杂波是制约对海雷达探测性能的主要因素之一,掌握其特性,具有十分重要的意义。经典海杂波统计模型在参数估计方法上以传统统计学理论为基础,在样本数较少的情况下,估计结果往往较差,导致建模准确度下降。此外,在复杂非均匀探测背景下,难以实现海杂波模型参数的准确实时估计。针对该问题,文章将深度神经网络模型引入海杂波参数估计领域,通过构建合理的模型,使其具备海杂波幅度分布模型的高精度参数估计能力。该方法采用直方图统计的方法进行数据预处理,合理划分输入数据标签的分组区间,构建数据集训练神经网络,并利用测试数据得到神经网络估计结果。仿真数据和X波段IPIX雷达实测数据验证结果表明,与传统数理统计估计方法相比,该算法明显提升了海杂波统计模型参数估计精度。     

基于非线性自适应滤波器的海杂波抑制技术

海杂波会严重影响雷达对海洋表面目标的检测。为了提高海洋表面目标的检测性能,基于非线性自适应滤波器,提出了海杂波抑制方法,实现了海杂波抑制。介绍了非线性自适应滤波器的原理以及利用梯度下降法训练滤波器的方法。利用IPIX雷达实测海杂波数据,分别针对岸基雷达和机载雷达,进行了此方法的仿真试验,从均方预测误差(MSE)和信杂比改善因子(IF)两个方面,分析了此方法的性能。并与基于线性预测的LMS算法进行了比较,得出了此方法对慢速目标的检测性能优于线性方法。     

HRR Detector for Slow-Moving Targets in Sea Clutter

The radar detection of targets in the presence of sea clutter has historically relied upon the radial velocity of targets with respect to the radar platform either by exploiting the relative target Dopplers (for targets with sufficient radial velocity) or by discerning the paths targets traverse from scan to scan. For targets with little to no radial velocity component, though, it can become quite difficult to differentiate targets from the surrounding sea clutter. This paper addresses the detection of slow-moving targets in sea clutter using a high resolution radar (HRR) such that the target has perceptible extent in range. Under the assumption of completely random sea clutter spikes based on an epsiv-contaminated mixture model with the signal and clutter powers known, optimal detection performance results from using the likelihood ratio test (LRT). However, for realistic sea clutter, the clutter spikes tend to be a localized phenomenon. Based upon observations from real radar data measurements, a heuristic approach exploiting a salient aspect of the idealized LRT is developed which is shown to perform well when applied to real measured sea clutter.     

A novel target detection approach based on adaptive radar waveform design

To resolve problems of complicated clutter, fast-varying scenes, and low signal-clutterratio (SCR) in application of target detection on sea for space-based radar (SBR), a target detection approach based on adaptive waveform design is proposed in this paper. Firstly, complicated sea clutter is modeled as compound Gaussian process, and a target is modeled as some scatterers with Gaussian reflectivity. Secondly, every dwell duration of radar is divided into several sub-dwells. Regular linear frequency modulated pulses are transmitted at Sub-dwell 1, and the received signal at this sub-dwell is used to estimate clutter covariance matrices and pre-detection. Estimated matrices are updated at every following sub-dwell by multiple particle filtering to cope with fast-varying clutter scenes of SBR. Furthermore, waveform of every following sub-dwell is designed adaptively according to mean square optimization technique. Finally, principal component analysis and generalized likelihood ratio test is used for mitigation of colored interference and property of constant false alarm rate, respectively. Simulation results show that, considering configuration of SBR and condition of complicated clutter, 9 dB is reduced for SCR which reliable detection requires by this target detection approach. Therefore, the work in this paper can markedly improve radar detection performance for weak targets.     

某雷达模拟器的目标与杂波信号模拟强度研究

建立了雷达模拟器中目标、地物杂波、海杂波、气象杂波的信号强度计算模型,根据相对运动关系解算出各目标与杂波信号的强度,并按时间流程存储在对应的数据表中,从而信号源将产生相应强度的信号注入雷达模拟台,以便后端雷达模拟台能在雷达威力覆盖范围内准确地显示出目标与杂波强度变化。通过仿真软件在雷达训练模拟器中的功能测试,实现了目标与杂波仿真效果,满足了雷达模拟训练的要求。     

基于导航雷达实测数据的CFAR检测算法分析

为提高导航雷达在复杂环境中的目标检测能力,研究了修正中值(MMD)检测器在导航雷达中的应用,并与经典非参量广义符号(GS)检测器和参量最小选择(SO)检测器的检测结果进行对比。仿真结果表明:GS检测器对海上单一目标有较好的检测性能,但是在多目标环境下的检测性能严重下降;SO检测器虽然对上述环境有较好的检测性能,但是由于杂波包络分布类型难以准确已知,杂波抑制能力较差;MMD检测器在多目标环境下有较好的检测性能和杂波抑制能力。     

Optimal polarimetric detection of radar target in a slowlyfluctuating environment of clutter

It is shown that in a situation where a radar target is distant enough from the radar and is included in a natural or artificial clutter environment in such a manner that the conventional detection methods fail, it is possible to improve the radar detection performance by using appropriate signal processing on two orthogonal polarization states. A CFAR (constant false alarm rate) polarimetric detection system based on the study of the polarization difference between clutter and target is proposed. Since the polarization state of the clutter echoes fluctuates slowly from cell to cell, an autoregressive model can be applied to the components of the polarization vector to predict the detection thresholds needed to follow the polarization state variation. The detection thresholds are determined to maintain a false alarm probability equal to 10^-6. The presence of a target registers as a significant variation of the estimation error of the polarization vector. Results obtained from measurements of simple and canonical targets with artificial clutter are presented, and these results validate the principle of polarimetric detection     

航迹规划中雷达探测空间的生成

从飞机突防习行任务规划出发，综合考虑地球曲率、陆地（或海洋）的反射和杂波干扰、大气折射和吸收损耗等因素的影响，采用临界散射截面法生成了对空警戒雷达在不同地貌、发现概率下，对不同雷达散射截面的目标的探测空间。计算并分析了飞行高度、目标雷达散射截面、发现概率和地貌等因素对雷达探测空间的影响，以便选择低探测概率的飞行走廓，这对制定和实施安全突防飞行策略有实际意义。     

Adaptive Radar Detection in Doubly Nonstationary Autoregressive Doppler Spread Clutter

The problem of adaptive radar detection in clutter which is nonstationary both in slow and fast time is addressed. Nonstationarity within a coherent processing interval (CPI) often precludes target detection because of the masking induced by Doppler spreading of the clutter. Across range bins (i.e., fast time), nonstationarity severely limits the amount of training data available to estimate the noise covariance matrix required for adaptive detection. Such difficult clutter conditions are not uncommon in complex multipath propagation conditions where path lengths can change abruptly in dynamic scenarios. To mitigate nonstationary Doppler spread clutter, an approximation to the generalized likelihood ratio test (GLRT) detector is presented wherein the CPI from the hypothesized target range is used for both clutter estimation and target detection. To overcome the lack of training data, a modified time-varying autoregressive (TVAR) model is assumed for the clutter return. In particular, maximum likelihood (ML) estimates of the TVAR parameters, computed from a single snapshot of data, are used in a GLRT for detecting stationary targets in possibly abruptly nonstationary clutter. The GLRT is compared with three alternative methods including a conceptually simpler ad hoc approach based on extrapolation of quasi-stationary data segments. Detection performance is assessed using simulated targets in both synthetically-generated and real radar clutter. Results suggest the proposed GLRT with TVAR clutter modeling can provide between 5–8 dB improvement in signal-to-clutter plus noise ratio (SCNR) when compared with the conventional methods.     

海杂波条件异方差特性分析与波动信息提取

由于低擦地角、高海况等易引起雷达海杂波序列的局部剧烈波动,传统的统计分布模型难以描述突然出现的具有冲激特性的强回波,因此,针对这一问题,将广义自回归条件异方差(Generalized Auto Regressive Conditional Heteroskedasticity,GARCH)模型引入海杂波建模中,通过 GARCH模型阶数步进搜索结合残差序列方差齐性检验,实现了海杂波数据的波动信息提取。经 X波段雷达实测数据验证,所提出的波动信息提取方法,可以很好地提取实测海杂波数据在局部区域或时间段内的波动信息,为特征检测方法设计提供有效的特征支撑。