海杂波视景仿真

雷达图像的生成在训练模拟器视景仿真研究中意义重大.在对海作战仿真中,海杂波仿真是对海雷达图像仿真研究的重点.文章在比较海杂波概率分布模型的基础上,探讨了复合K分布实现方法,并应用Vega和Creator等软件实现海杂波视景仿真,生成了由海杂波形成的雷达图像,取得了较好效果,具有一定的借鉴意义.     

末制导雷达抗舷外有源诱饵干扰研究

针对舷外有源雷达诱饵干扰末制导雷达的原理,提出了末制导雷达发射复杂信号对抗舷外有源雷达诱饵的方法,建立了发射信号模型,并从时域参数测量和时频分析两方面仿真分析了发射信号的反侦察能力;同时,对末制导雷达去干扰能力进行了仿真分析,验证了此种发射信号抗舷外有源雷达诱饵的有效性。     

有源对消隐身系统设计研究

针对有源对消隐身要求的系统延时短、反应速度快、信号参数测量和对消波幅相控制精度高的特点,设计了一个基于相控阵技术、数字射频存储器(DRFM)和现场可编程门阵列(FPGA)的有源对消系统。为了解决目标雷达散射截面计算量太大、不能有流水线延迟和难以实现实时计算等问题,采用离线计算的方法,预先建立目标的全向雷达散射截面(RCS)数据库、杂波数据库和噪声数据库,由FPGA根据测得的雷达信号参数在数据库中查找到相应的目标回波数据,实时调整对消波的幅度和相位,使对方的雷达接收机始终处于合成方向图的零点。最后通过仿真计算验证了该设计方案的有效性。     

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。     

导弹末制导雷达搜索图研究

以远程反舰导弹为研究对象,运用概率统计理论、优化设计方法,研究远程反舰导弹末制导雷达目标搜捕问题。构建典型目标的数学模型,提出末制导雷达搜索图设计方案,得出了目标命中概率和截获概率的计算方法。     

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。     

反舰导弹末制导雷达最小方位搜索范围确定模型

针对目前各国日益重视电子干扰而反舰导弹末制导雷达搜索范围却呈现逐步扩大的趋势,进行了最小方位搜索范围确定模型的研究。把目标机动范围和目标指示精度误差作为圆分布来处理,按照捕捉概率不小于0.99的要求,利用解析算法,建立了反舰导弹末制导雷达最小搜索范围确定的基本模型,并在把主要误差综合为目标指示精度和侧向横移两类误差的基础上,对模型进行了修正。对开机距离为30 km,35 km和40 km时不同条件下高亚声速、超声速反舰导弹末制导雷达的最小方位搜索范围进行了仿真。结果显示,高亚声速反舰导弹末制导雷达的最小搜索范围在±40°之内,超声速反舰导弹在±27°之内,对应比某些现役反舰导弹末制导雷达的搜索范围要小。     

目标机动对反舰导弹目标捕捉概率的影响

根据反舰导弹末制导雷达捕捉目标和舰艇机动的原理,建立了目标机动条件下末制导雷达捕捉目标的计算模型,仿真结果显示,对中远程反舰导弹而言,目标机动对目标捕捉概率有显著影响。     

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。     

基于落角约束的超声速导弹制导方案研究

针对超声速导弹具有落角约束条件下的制导问题,提出了一种新的设计方案.首先,在中制导俯冲过程中,采用攻击预先设定的虚拟目标方案,达到期望的中制导末端性能指标;然后,开始末制导俯冲段,雷达开机实时攻击实际目标,使导弹在需用过载和导引头框架角约束条件下,以期望落角命中目标.仿真结果表明,该制导律具有期望的性能要求,易于工程实现.     

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。     

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。     

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.     

Time-frequency method for detecting an accelerating target in sea clutter

The authors design a time-frequency (TF) method for use in high-frequency surface-wave radar (HFSWR) for detecting a small accelerating target in sea clutter. The clutter is modelled by pseudo targets moving with Bragg velocity towards and away from the radar. The design is based on the Wigner distribution (WD) defined by Chan (type-III WD, in our terminology) rather than the WD defined by Claasen and Mecklenbrauker (1980) (2times type-I WD, in our terminology). Like the type-I WD, the type-III WD also concentrates a chirp signal onto a straight line in the TF plane. The type-III WD has the following advantages: 1) Its range of unambiguously measurable frequencies (RUMF) is [-pi,pi] rad/s, whereas for the type-I WD the RUMF is [-pi/2,pi/2] rad/s. 2) It allows a target separated from the clutter by pi rad/s to be detected, whereas the type-I WD coalesces such a target with the clutter and thereby mask it. An ambiguity function (AF) was defined corresponding to the type-III WD and use it to derive a smoothed type-III WD that mitigates the clutter. The smoothed type-III WD method is applied to real radar data and shown to be superior to the conventional Fourier transform method. The advantages of the type-III WD over the type-I WD are also demonstrated. The design principles laid out in the paper can also be used to develop a TF method for use in air traffic control radar (ATCR) for detecting an accelerating target in land clutter     

Detection of small objects in clutter using a GA-RBF neural network

Detection of small objects in a radar or satellite image is an important problem with many applications. Due to a recent discovery that sea clutter, the electromagnetic wave backscatter from a sea surface, is chaotic rather than purely random, computational intelligence techniques such as neural networks have been applied to reconstruct the chaotic dynamic of sea clutter. The reconstructed sea clutter dynamical system which usually takes the form of a nonlinear predictor does not only provide a model of the sea scattering phenomenon, but it can also be used to detect the existence of small targets such as fishing boats and small fragments of icebergs by observing abrupt changes in the prediction error. We applied a genetic algorithm (GA) to obtain an optimal reconstruction of sea clutter dynamic based on a radial basis function (RBF) neural network. This GA-RBF uses a hybrid approach that employes a GA to search for the optimum values of the following RBF parameters: centers, variance, and number of hidden nodes, and uses the least square method to determine the weights. It is shown here that if the functional form of an unknown nonlinear dynamical system can be represented exactly using an RBF net (i.e., no approximation error), this GA-RBF approach can reconstruct the exact dynamic from its time series measurements. In addition to the improved accuracy in modeling sea clutter dynamic, the GA-RBF is also shown to enhance the detectability of small objects embedded in the sea. Using real-life radar data that are collected in the east coast of Canada by two different radar systems: a ground-based radar and a satellite equipped with synthetic aperture radar (SAR), we show that the GA-RBF network is a reliable detector for small surface targets in various sea conditions and is practical for real-life search and rescue, navigation, and surveillance applications     

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.     

IPIX雷达海尖峰统计特性研究

根据雷达海尖峰构成原理,以K分布为模型,提出了海尖峰的统计特性分析方法,并使用该方法对IPIX雷达实测海杂波数据进行了统计特性分析,分析结果证明了该方法的有效性。     

Radar Properties of Non-Rayleigh Sea Clutter

Measurements of sea clutter at low grazing angles using high- resolution radar show that the probability density p(x) of envelope detected sea clutter is not Rayleigh. Using the composite surface scattering model, a special varying clutter density p(x|?0) is proposed and is used to explain the non-Rayleigh nature of clutter. Since the clutter distribution has an enormous effect on the performance of a radar, the variation of the clutter densities, p(x) and p(x|?0), with various radar parameters such as frequency, pulsewidth, and polarization is found. Finally, a simulation of the composite surface scattering model is performed, and it verifies the effect of the various parameters on p(x).     

基于嵌入式仿真的雷达训练系统设计

介绍了嵌入式仿真技术及其发展,将嵌入式仿真与雷达模拟训练相结合,构成了能够嵌入到机械扫描雷达实装的模拟训练系统。描述了对嵌入式仿真训练系统的结构组成以及部分模块的功能,研究了模拟雷达视频回波数据的方法和模型,包括目标回波、地物杂波、海杂波、气象杂波、有源干扰和接收机内部噪声,利用数学模型计算回波的强度、方位、距离等特性,调制实际录取的回波数据,生成与态势设置参数相应的模拟回波数据,能够对信号处理操作和抗干扰操作做出响应。通过对视频回波进行仿真,由终端显示画面可知模拟的回波数据具有较高的逼真度,经测试模拟视频回波能够被雷达显控终端识别。