2014-02-10 09:34:18 +08:00
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function h = covarianceEllipse(x,P,color, k)
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2012-09-08 13:28:25 +08:00
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% covarianceEllipse plots a Gaussian as an uncertainty ellipse
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2012-07-28 03:02:11 +08:00
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% Based on Maybeck Vol 1, page 366
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% k=2.296 corresponds to 1 std, 68.26% of all probability
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% k=11.82 corresponds to 3 std, 99.74% of all probability
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%
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2013-10-29 22:34:41 +08:00
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% covarianceEllipse(x,P,color,k)
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2012-07-28 03:02:11 +08:00
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% it is assumed x and y are the first two components of state x
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2013-10-29 22:34:41 +08:00
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% k is scaling for std deviations, defaults to 1 std
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2012-07-28 03:02:11 +08:00
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2015-01-23 09:39:02 +08:00
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hold on
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2012-07-28 03:02:11 +08:00
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[e,s] = eig(P(1:2,1:2));
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s1 = s(1,1);
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s2 = s(2,2);
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2013-10-29 22:34:41 +08:00
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if nargin<4, k = 2.296; end;
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2012-07-28 03:02:11 +08:00
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[ex,ey] = ellipse( sqrt(s1*k)*e(:,1), sqrt(s2*k)*e(:,2), x(1:2) );
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2014-02-10 09:34:18 +08:00
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h = line(ex,ey,'color',color);
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2012-07-28 03:02:11 +08:00
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function [x,y] = ellipse(a,b,c);
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% ellipse: return the x and y coordinates for an ellipse
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% [x,y] = ellipse(a,b,c);
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% a, and b are the axes. c is the center
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global ellipse_x ellipse_y
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if ~exist('elipse_x')
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q =0:2*pi/25:2*pi;
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ellipse_x = cos(q);
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ellipse_y = sin(q);
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end
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points = a*ellipse_x + b*ellipse_y;
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x = c(1) + points(1,:);
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y = c(2) + points(2,:);
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end
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2015-01-23 09:39:02 +08:00
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end
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