forked from Archive/PX4-Autopilot
62 lines
1.6 KiB
Matlab
62 lines
1.6 KiB
Matlab
function [xapo1,Papo1] = position_estimator(u,z,xapo,Papo,gps_covariance,predict_only) %if predit_onli == 1: no update step: use this when no new gps data is available
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%#codegen
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%%initialization
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%use model F=m*a x''=F/m
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% 250Hz---> dT = 0.004s
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%u=[phi;theta]
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%x=[px;vx;py;vy];
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%%------------------------------------------
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dT=0.004;
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%%------------------------------------------------
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%R_t=[1,-r*dT,q*dT;r*dT,1,-p*dT;-q*dT,p*dT,1];
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F=[ 1, 0.004, 0, 0, 0, 0;
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0, 1, 0, 0, 0, 0;
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0, 0, 1, 0.004, 0, 0;
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0, 0, 0, 1, 0, 0;
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0, 0, 0, 0, 1, 0.004;
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0, 0, 0, 0, 0, 1];
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B=[ 0, -0.1744;
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0, -87.2;
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0.1744, 0;
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87.2, 0;
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0, 0;
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0, 0];
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H=[1,0,0,0,0,0;
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0,0,1,0,0,0;
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0,0,0,0,1,0];
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Q=[1e-007 ,0 ,0 ,0 ,0 ,0;
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0 ,1 ,0 ,0 ,0 ,0;
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0 ,0 ,1e-007 ,0 ,0 ,0;
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0 ,0 ,0 ,1 ,0 ,0
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0 ,0 ,0 ,0 ,1e-007 ,0;
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0 ,0 ,0 ,0 ,0 ,1]; %process Covariance Matrix
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R=[gps_covariance(1), 0, 0;
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0, gps_covariance(2), 0;
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0, 0, gps_covariance(3)]; %measurement Covariance Matrix
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%%prediction
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xapri=F*xapo+B*u;
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Papri=F*Papo*F'+Q;
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if 1 ~= predict_only
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%update
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yr=z-H*xapri;
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S=H*Papri*H'+R;
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K=(Papri*H')/S;
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xapo1=xapri+K*yr;
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Papo1=(eye(6)-K*H)*Papri;
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else
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Papo1=Papri;
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xapo1=xapri;
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end |