登录
首页 » Visual C++ » hongwaileida

hongwaileida

于 2012-03-06 发布 文件大小:1456KB
0 343
下载积分: 1 下载次数: 55

代码说明:

  针对粒子概率假设密度(PH D)滤波算法在虚警、漏检情况下,b标状态估计不稳定和b标可观测性车弱的问题,提出了一种基于序贯融合的粒子PH D滤波方法,利用雷达和红外传感器多目标进行融合跟踪杏基本思想是先对红外传感器进行粒子PH D滤波,丙将红外传感器滤波结果作为雷达的预测值,然后利用P达观测的数据进行更新,这样通过雷达和红外传感器交替上作保证目标状态的可观测性,从滤波器输出结身即可得到目标的状态信息仿真结果表明,在虚警、漏检和密集目标环境下,该方法是有效的和稳健的(The problem of target state estimation instability and observability weakerin the presence offalse alarms and missed detection was deal with. On the basis of sequential fusion, a particleprobabil- ity hypothesis density(PHD) filter for multrsensor multrtarget tracking was proposed. Observed da to collected from the infrared sensor was estimated with the particle PHD filter. Then the results from the filter were set as the radar predicted value by the radar observations. The multrtarget state can be updated to guarantee observing the target state. In this way, the global state is updated at the fusion center. Simulation results show that the proposed algorithm is effective and robust under the false warning, omission and concentrated target environment. )

文件列表:

红外-雷达融合程序(网上下的最简单加权)
.....................................\Asynchronism_IR.m,2967,2011-11-20
.....................................\Asynchronism_Radar.asv,3329,2011-12-16
.....................................\Asynchronism_Radar.m,3356,2011-12-16
.....................................\ceshi.m,615,2011-11-20
.....................................\EKF_IR.m,5690,2011-11-20
.....................................\EKF_Radar.m,5761,2011-11-20
.....................................\fusion_asyn.m,5984,2011-11-20
.....................................\source.m,2198,2011-11-20
.....................................\sourceIR.m,4181,2011-11-20
.....................................\sourceRadar.m,4206,2011-11-20
.....................................\数据
.....................................\....\745.mat,60520,2011-11-20
.....................................\....\EKF_IR.mat,381099,2011-11-20
.....................................\....\EKF_Radar.mat,808643,2011-11-20
.....................................\....\source.mat,18647,2011-11-20
.....................................\....\sourceIR.mat,70849,2011-11-20
.....................................\....\sourceRadar.mat,140462,2011-11-20
.....................................\程序说明.txt,215,2011-11-20
.....................................\详细说明.txt,338,2011-11-20

下载说明:请别用迅雷下载,失败请重下,重下不扣分!

发表评论

0 个回复

  • tree1
    四叉树分割 opencv 编写 读入灰度图 进行递归分割(Quadtree segmentation opencv read into grayscale prepared for recursive partitioning)
    2021-04-27 21:08:45下载
    积分:1
  • ImageProcess
    实现bmp图像读入和写出,彩色图像灰度化,直方图均衡化(Implement bmp image read and write, color image graying, histogram equalization)
    2015-11-02 19:26:29下载
    积分:1
  • EllipseCir
    椭圆拟合,输入中心坐标及椭圆长半轴和短半轴即可画出相应椭圆(ellipse fitting)
    2013-12-18 23:49:16下载
    积分:1
  • sarMatch
    说明:  基于边缘特征的SAR图像与光学图像匹配,测度为Hausdorff距离(SAR images based on edge features and optical image matching, for the Hausdorff distance measure )
    2020-10-12 09:57:32下载
    积分:1
  • avisample
    生成avi视频截图序列。设置截图时长,截图频率,截图类型的参数。(Generate avi video sampling sequence.Screenshot duration, frequency and types of parameters are allowed to set freedom.)
    2013-07-10 17:18:11下载
    积分:1
  • 1-(5)
    图形处理,Visual C++数字图像识别技术典型案例源代码 5(Graphics processing , the Visual C++ digital image recognition technology to a typical case of source code 5)
    2012-02-29 11:13:02下载
    积分:1
  • zi
    说明:  自由曲面光学透镜的图像变换面形测量系统与精度建模(Free-form optical lens image transformation shape measurement system with precision modeling)
    2013-03-07 09:08:13下载
    积分:1
  • HOG+SVM进行图片中行人检测
    说明:  行人检测HOG+SVM进行图片中行人检测,提供训练用的pos和neg样本,效果还可以;没有SVM工具箱的,压缩包里已经提供了,安装一下即可(Pedestrian detection HOG + SVM for pedestrian detection in pictures, providing POS and neg samples for training, the effect is good; without SVM toolbox, the compression package has been provided, just install it.)
    2020-10-30 16:09:56下载
    积分:1
  • PCA
    这是关于pca的文件,说明实现pca的降维(This is the file on pca, achieve pca dimensionality reduction)
    2020-07-02 01:40:01下载
    积分:1
  • two
    :植物种类识别方法主要是根据叶片低维特征进行自动化鉴定。然而,低维特征不能全面描述叶片信息,识别准确率低,本文提 出一种基于多特征降维的植物叶片识别方法。首先通过数字图像处理技术对植物叶片彩色样本图像进行预处理,获得去除颜色、虫洞、 叶柄和背景的叶片二值图像、灰度图像和纹理图像。然后对二值图像提取几何特征和结构特征,对灰度图像提取 Hu不变矩特征、灰 度共生矩阵特征、局部二值模式特征和 Gabor 特征,对纹理图像提取分形维数,共得到 2183 维特征参数。再采用主成分分析与线性 评判分析相结合的方法对叶片多特征进行特征降维,将叶片高维特征数据降到低维空间。使用降维后的训练样本特征数据对支持向量 机分类器进行训练(plant species identification method is mainly based on blade automatic identification of low dimensional characteristics.However, can not fully describe blade low-dimensional feature information, identification accuracy is low, in this paper A kind of plant leaves recognition method based on multiple feature dimension reduction.First by digital image processing technology to the plant leaf color sample image preprocessing, obtain background color removal, wormhole, petioles, and the blades of a binary image, gray image and texture image.Then the binary image to extract the geometric characteristics and characteristics of structure and characteristics of gray image extraction Hu moment invariants, gray co-occurrence matrix feature, local binary pattern features and Gabor, to extract the fractal dimension of texture image, get 2183 d characteristic parameters.By principal component analysis and linear uation analysis method of combining the characteristics of blade more feature dimensi)
    2017-02-28 09:57:50下载
    积分:1
  • 696516资源总数
  • 106914会员总数
  • 0今日下载