利用Visual C＋＋和Direct3D设计雷达显示器

利用Visual C＋＋和Direct3D对某雷达显示器的实现过程作了详细论述,包括数据采集、PPI型显示器、A型显示器、B型显示器、余晖显示、航迹显示等。通过试验证明,采用Direct3D绘图方式比采用GDI绘图方式效果好,更适用于数据处理量大、天线扫描速度快的雷达显示器。     

一种雷达和摄像机的空间标定方法

多传感器融合技术已经广泛应用在智能汽车环境感知领域中;雷达和摄像机的空间标定是伴随信息实时融合的道路检测技术的基础;结合智能汽车的实际应用,提出了针对激光雷达和摄像机的空间标定方法;通过特制的标定板来获得雷达数据和图像数据,选取激光雷达坐标系作为世界坐标系,通过参数拟合的方法来求取图像坐标系与雷达坐标系的变换关系,进而实现两种传感器的空间配准;该方法只需要标定板就能够完成激光雷达和摄像机的空间标定,标定精度高,实现了多个传感器世界坐标系的统一,避免了后续处理中数据解释的二义性;实验结果表明这种方法简单准确,满足系统要求。     

基于FPGA的雷达状态参数采集系统设计与实现

为使雷达回波模拟系统能够逼真地模拟真实作战环境,有效地对雷达各分系统进行测试,提出了雷达状态参数采集电路的设计方案,并给出了其软硬件实现;该方案以FPGA为核心,解决了不同状态参数的实时性采集问题,并通过制定串行传输协议,避免了数据传输过程中的冲突,保证了各状态参数传输的准确性,输出接口采用LVDS标准接口,确保了各状态参数的高速长距离传输;实验结果表明,该系统工作稳定,能够准确、实时地采集并传输雷达状态参数,且便于与其他数字电路的集成,满足系统设计的要求。     

小波神经网络在雷达故障诊断中的应用研究

根据某型雷达接收机的信号特点,提出了基于小波神经网络和专家知识相结合的雷达智能故障诊断方法,探讨了该方法在某型雷达接收机故障诊断中的应用,采样信号经过小波去噪和小波特征向量提取后再进行归一化处理,作为小波神经网络的输入向量,小波神经网络隐含层的激活函数选用小波函数,完成雷达接收机典型故障的诊断;MATLAB实例仿真结果表明,该方法诊断准确,智能化水平高,有很好的自学习能力,提高了故障诊断的正确性和效率。     

相控阵PD雷达目标检测的实时空间滤波算法

针对弹载相控阵PD制导雷达的目标搜索与检测应用,建立了回波信号模型以及基于子阵的信号处理模型;提出了一种旁瓣杂波区位置估计以及在旁瓣杂波区检测目标的实时空间滤波新算法。该算法采用方位、俯仰方向上的分步降维处理,以一定的滤波性能损失换取运算开销的显著降低;通过理论分析比较了该算法与常规最优空间滤波算法的运算复杂度;通过计算机仿真实验比较了该算法与常规PD雷达的信号积累算法、相控阵PD雷达的最优空间滤波算法的杂波抑制性能。     

高分辨雷达信号的平移不变KPCA特征提取算法

研究高分辨雷达信号特征提取,针对传统提取平移不变特征存在信息损失量大、识别的准确率低的问题,提出了一种平移不变KPCA特征提取算法。首先计算高分辨雷达信号的原点矩,并在低信息损失的前提下利用高分辨雷达信号相对原点矩的位置来描述原信号,从而消除高分辨雷达信号的平移敏感性。然后结合KPCA特征提取算法得到平移不变的特征信号。最后应用SVM分类器对特征信号进行分类识别。实验证明,改进算法识别率高于雷达目标识别系统中的传统特征提取算法,略低于KPCA特征提取算法,且在常用雷达探测距离内都能够保持较高的识别率。     

Edge diffraction correction for 3D scattering center modeling based on the shooting and bouncing ray technique

In the traditional scattering center extraction method based on the shooting and bouncing ray(SBR) technique,only the physical optics contribution of the target is considered.However,the physical optics method is unable to describe the contribution of the actual edge diffraction.By comprehensively considering the specular reflection and edge diffraction contribution of the target,an edge diffraction correction method for 3D scattering center modeling based on the SBR technique is proposed.Using the SBR technique and combining the image domain ray tube integration and equivalent edge currents method,the edge diffraction correcting formula for the 3D inverse synthetic aperture radar image is derived.Simulation results show that the proposed method is able to effectively improve the modeling accuracy of the 3D scattering center.     

Method for discrimination of false targets in multistation radar systems based on the deep neural network

For the existing jamming discrimination methods for multistation radar systems,only the single feature of target echo space correlation is utilized as the metric,which leads to insufficient comprehensiveness of feature extraction,so that effectiveness and universality are insufficient for the discrimination algorithm.In this paper,an identification method in multistatic radar systems based on the deep neural network is proposed.This method combines the characteristics of multistatic radar systems cooperative detection technology,which has many available resources and strong scheduling ability in space,time and frequency domain,with the strong model learning and feature representation ability in the process of information processing on the deep neural network,so that it can effectively apply to the field of anti-deception jamming.Full use is made of unknown information about echo data to obtain more multi-dimensional,more comprehensive,more complete and deeper feature differences besides correlation,so as to achieve a better jamming discrimination effect.Simulation results show that the proposed method can effectively reduce the influence of noise and pulse number on the jamming discrimination performance.At the same time,the limitation of the target echo correlation coefficient on anti-jamming technology under nonideal conditions is alleviated,which broadens the boundary conditions of the application process.     

Improved ionospheric clutter classification method based on fuzzy C-means clustering

The ionospheric clutter is a time-varying,non-stationary and non-Gaussian complex clutter in the high-frequency surface-wave radar(HFSWR) system and its suppression is a daunting task.Due to the complexity of the ionospheric clutter,the single clutter suppression algorithm cannot suppress the clutter effectively.Classification of the complex ionospheric clutter according to different characteristics can improve the performance of ionospheric clutter suppression significantly.After a complete analysis of the characteristics of ionospheric clutter,this paper proposes an improved ionospheric clutter classification method based on fuzzy C-means clustering.Experimental results show that the proposed method has a better performance than the traditional algorithm in clustering the ionospheric clutter.     

A Brief Introduction on Joint Radar and Communication Systems

Joint radar and communication(JRC) technology is gradually becoming an essential approach to alleviating spectral congestion. Radar and communications systems were designed with common spectral and hardware resources to reduce size, improve performance, reduce cost, and decongest the spectrum. Various approaches have been proposed to achieve the coexistence of radar and communication systems. This paper mainly focuses on the research directions of radar communication coexistence(RCC) and dual-function radar communication systems(DFRC) in JRC technology. We summarize and analyze the existing research problems in the JRC era. According to the characteristics and advantages of JRC technology, we highlight several potentials in military and commercial applications.