Fundamentals of Kalman Filtering A Practical Approach Third Edition.pdf
是我从网上找的一本关于卡尔曼滤波的教材
2020-01-30 03:03:15
9.07MB
1
目标跟踪问题的应用背景是雷达数据处理，即雷达在搜索到目标并记录目标的位置数据,
对测量到的目标位置数据（称为点迹）进行处理，自动形成航迹，并对目标在下一时刻的位置进行预测。
下文简要讨论了用Kalman滤波方法对单个目标航迹进行预测，并借助于Matlab仿真工具，对实验的效果进行评估。
2020-01-10 03:06:43
119KB
1
卡尔曼滤波经典论文，卫星姿态控制大牛Landis Markley发表的卡尔曼滤波在卫星姿态控制应用的论文，学习卡尔曼滤波算法很好的参考资料！
2020-01-03 11:20:52
925KB
1
带高斯白噪声的Kalman滤波Matlab代码，每一步都有详细的注释，和kalman滤波的五个公式对应。并有高斯白噪声的产生函数，function G = CreateGauss(E,D,M,N) %产生均值为E,方差为D,MxN的高斯白噪声矩阵
2019-12-30 03:01:27
1KB
1
data
linear filtering problem [Kalman60]. Since that time, due in large part to advances in digital
computing, the
Kalman filter
has been the subject of extensive research and application,
particularly in the area of autonomous or assisted navigation. A very “friendly” introduction to the
general idea of the Kalman filter can be found in Chapter 1 of [Maybeck79], while a more complete
introductory discussion can be found in [Sorenson70], which also contains some interesting
historical narrative. More extensive references include [Gelb74; Grewal93; Maybeck79; Lewis86;
Brown92; Jacobs93].
2019-12-21 22:25:07
238KB
1
camshift+kalman视频跟踪matlab代码，主要是对人脸的识别跟踪，也可以自己拍些合适的视频测试，last.m是主函数，程序是通的，下载就能使用。
2019-12-21 22:18:09
2.17MB
1
clear all
N=100;
T=4*pi/N;
t=0:4*pi/N:4*pi-T;
w=2*pi/(24*3600);
X1=zeros(15,N);
X2=zeros(15,N);
L=zeros(6,N);
X2(:,1)=[1,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
X1(:,1)=X2(:,1);
E=eye(15);
W=[0 -w 0;w 0 0;0 0 0];
A=zeros(15,15);
A(1:3,4:6)=eye(3);
A(4:6,4:6)=-2*W;
A(7:9,7:9)=-W;
for i=10:12
A(i,i)=-1/7200;
end
for i=13:15
A(i,i)=-1/1800;
end
A=eye(15)+A*T+A*A*(T.^2)/2;
Z1=zeros(15,15);
Z2=eye(15);
R=eye(6);
Q=zeros(15,15);
Q(15,15)=1;
K=zeros(15,6);
H=zeros(6,15);
for i=1:6
H(i,i)=1;
end
for i=1:N
L(:,i)=zeros(6,1);
L(1,i)=randn(1);
end
for i=2:N
X1(:,i)=A*X2(:,i-1);
Z1=A*Z2*A'+Q;
K=Z1*H'*inv(H*Z1*H'+R);
X2(:,i)=X1(:,i)+K*(L(:,i)-H*X1(:,i));
Z2=[E-K*H]*Z1;
end
plot(t,L(1,:),'g*');
hold on;
plot(t,X1(1,:),'r*');
2019-12-21 22:14:53
805B
1