35 lines
1.1 KiB
Matlab
35 lines
1.1 KiB
Matlab
function h = covarianceEllipse(x,P,color, k)
|
|
% covarianceEllipse plots a Gaussian as an uncertainty ellipse
|
|
% Based on Maybeck Vol 1, page 366
|
|
% k=2.296 corresponds to 1 std, 68.26% of all probability
|
|
% k=11.82 corresponds to 3 std, 99.74% of all probability
|
|
%
|
|
% covarianceEllipse(x,P,color,k)
|
|
% it is assumed x and y are the first two components of state x
|
|
% k is scaling for std deviations, defaults to 1 std
|
|
|
|
[e,s] = eig(P(1:2,1:2));
|
|
s1 = s(1,1);
|
|
s2 = s(2,2);
|
|
if nargin<4, k = 2.296; end;
|
|
[ex,ey] = ellipse( sqrt(s1*k)*e(:,1), sqrt(s2*k)*e(:,2), x(1:2) );
|
|
h = line(ex,ey,'color',color);
|
|
|
|
function [x,y] = ellipse(a,b,c);
|
|
% ellipse: return the x and y coordinates for an ellipse
|
|
% [x,y] = ellipse(a,b,c);
|
|
% a, and b are the axes. c is the center
|
|
|
|
global ellipse_x ellipse_y
|
|
if ~exist('elipse_x')
|
|
q =0:2*pi/25:2*pi;
|
|
ellipse_x = cos(q);
|
|
ellipse_y = sin(q);
|
|
end
|
|
|
|
points = a*ellipse_x + b*ellipse_y;
|
|
x = c(1) + points(1,:);
|
|
y = c(2) + points(2,:);
|
|
end
|
|
|
|
end |