基本信息
源码名称:卡尔曼滤波目标跟踪(matlab代码)
源码大小:1.60KB
文件格式:.m
开发语言:MATLAB
更新时间:2020-03-08
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源码介绍
卡尔曼滤波例子
卡尔曼滤波例子
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Kalman滤波在船舶GPS导航定位系统中的应用 % 详细原理介绍及中文注释请参考: % 《卡尔曼滤波原理及应用-MATLAB仿真》,电子工业出版社,黄小平著。 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% function Kalman clc;clear; T=1; N=80/T; X=zeros(4,N); X(:,1)=[-100,2,200,20]; Z=zeros(2,N); Z(:,1)=[X(1,1),X(3,1)]; delta_w=1e-2; Q=delta_w*diag([0.5,1,0.5,1]) ; R=100*eye(2); F=[1,T,0,0;0,1,0,0;0,0,1,T;0,0,0,1]; H=[1,0,0,0;0,0,1,0]; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% for t=2:N X(:,t)=F*X(:,t-1) sqrtm(Q)*randn(4,1); Z(:,t)=H*X(:,t) sqrtm(R)*randn(2,1); end Xkf=zeros(4,N); Xkf(:,1)=X(:,1); P0=eye(4); for i=2:N Xn=F*Xkf(:,i-1); P1=F*P0*F' Q; K=P1*H'*inv(H*P1*H' R); Xkf(:,i)=Xn K*(Z(:,i)-H*Xn); P0=(eye(4)-K*H)*P1; end for i=1:N Err_Observation(i)=RMS(X(:,i),Z(:,i)); Err_KalmanFilter(i)=RMS(X(:,i),Xkf(:,i)); end figure hold on;box on; plot(X(1,:),X(3,:),'-k'); plot(Z(1,:),Z(2,:),'-b.'); plot(Xkf(1,:),Xkf(3,:),'-r '); legend('真实轨迹','观测轨迹','滤波轨迹') figure hold on; box on; plot(Err_Observation,'-ko','MarkerFace','g') plot(Err_KalmanFilter,'-ks','MarkerFace','r') legend('滤波前误差','滤波后误差') %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% function dist=RMS(X1,X2); if length(X2)<=2 dist=sqrt( (X1(1)-X2(1))^2 (X1(3)-X2(2))^2 ); else dist=sqrt( (X1(1)-X2(1))^2 (X1(3)-X2(3))^2 ); end %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%