Change detection in synthetic aperture radar images based on unsupervised artificial immune systems

In this paper, we propose a novel change detection method for synthetic aperture radar images based on unsupervised artificial immune systems. After generating the difference image from the multitemporal images, we take each pixel as an antigen and build an immune model to deal with the antigens. By continuously stimulating the immune model, the antigens are classified into two groups, changed and unchanged. Firstly, the proposed method incorporates the local information in order to restrain the impact of speckle noise. Secondly, the proposed method simulates the immune response process in a fuzzy way to get an accurate result by retaining more image details. We introduce a fuzzy membership of the antigen and then update the antibodies and memory cells according to the membership. Compared with the clustering algorithms we have proposed in our previous works, the new method inherits immunological properties from immune systems and is robust to speckle noise due to the use of local information as well as fuzzy strategy. Experiments on real synthetic aperture radar images show that the proposed method performs well on several kinds of difference images and engenders more robust result than the other compared methods.     

Stereo matching cost computation based on nonsubsampled contourlet transform

A new matching cost computation method based on nonsubsampled contourlet transform (NSCT) for stereo image matching is proposed in this paper. Firstly, stereo image is decomposed into high frequency sub-band images at different scales and along different directions by NSCT. Secondly, by utilizing coefficients in high frequency domain and grayscales in RGB color space, the computation model of weighted matching cost between two pixels is designed based on the gestalt laws. Lastly, two types of experiments are carried out with standard stereopairs in the Middlebury benchmark. One of the experiments is to confirm optimum values of NSCT scale and direction parameters, and the other is to compare proposed matching cost with nine known matching costs. Experimental results show that the optimum values of scale and direction parameters are respectively 2 and 3, and the matching accuracy of the proposed matching cost is twice higher than that of traditional NCC cost.     

一款紧凑增强型可变阻抗电磁带隙结构

基于传统AI-EBG结构,提出了一种小尺寸的增强型电磁带隙结构,实现了从0.5~9.4 GHz的宽频带-40 dB噪声抑制深度,且下截止频率减少到数百MHz,可有效抑制多层PCB板间地弹噪声。文中同时研究了EBG结构在高速电路应用时的信号完整性问题,使用差分信号方案可改善信号完整性。     

一种PD雷达动目标模拟与微波测控系统

介绍了一种基于PC／104总线，具有GPIB程控功能，采用无内部微波源体制，通过在雷达载频上调制多普勒频率模型目标速度信息，延迟雷达发射机触发脉冲模拟目标距离信息并具有微波功率精确定标与衰减功能的PD雷达动目标模拟与微波测控系统。     

利用AutoCAD编制电气CAD

介绍如何利用AutoCAD开发适合电气专业使用的CAD系统，通过编制电气CAD的功能菜单，构造电气元件库，增强CAD的专业性能。编制电气CAD可以有效地统一本单位电气制图标准，方便电气工程师使用CAD进行专业设计。     

传感器管理及其在相控阵雷达中的应用

传感器管理是数据融合的一部分。介绍了传感器管理的概念和框架 ,概述了国内外传感器管理算法的研究现状。主要工作是针对相控阵雷达这一传感器 ,通过对其不同工作模式以及不同参数的管理 ,来说明传感器管理的原理。提出了一种新的自适应采样周期算法 ,仿真结果表明该算法的优越性     

基于扩展分形和CFAR特征融合的SAR图像目标识别

研究了多信息融合技术在SAR图像目标识别中的应用。将扩展分形特征(Extended Fractal)与双参数恒虚警特征(Double Parameter CFAR)形成的多信息进行融合处理。运用Dempster-Shafer证据理论，在决策层对SAR图像中的像素进行识别分类。实验结果表明通过融合对像素分类的准确性明显好于单特征的检测结果，减少了虚警概率，提高了系统的识别能力。     

基于主体外部轮廓的照片分割算法

在实际应用中常常需要将人像从照片的背景中有效地分割出来，通常的做法是通过提取照片中人像各部分特征来实现分割，其缺陷是计算复杂度较大，分割效果受各种干扰因素影响很大。现提出了一种基于主体外部轮廓信息的照片分割算法，通过梯度锐化、边缘保护、临近像素点相似度比较来确定图像的边界，该算法对于具有相对均匀背景的照片具有较高的计算效率。     

基于WVD的防空雷达直升机信号特征分析

基于直升机目标旋转部件的调制模型，本文针对防空雷达提出了分析直升机信号特征的一种新方法——WVD法，并对直升机目标旋转部件调制回波信号在不同噪声情况下加以仿真分析，结果表明：用WVD分析雷达回波中直升机信号特征是一种非常有效的方法。     

利用信息融合方法的三维特征提取

本文提出了一种基于信息融合的物体三维特征的提取方法，该方法利用两幅互相配准的三维测距图像和灰度图像，来提取多面体的三维特征。首先，通过分析灰度图像中的灰度变化及测距图像中的测距值变化，分别求取各自图像中物体的特征点及特征边；然后，利用两配准图像之间的对应关系，求得所有特征点、面与多边形在三维测距图像中的三维表示；接着，通过分析三维测距图像中所测得的各候选平面上特定点与边处的曲率及法向，验证候选平面