mirror of https://github.com/ArduPilot/ardupilot
91 lines
2.6 KiB
Matlab
91 lines
2.6 KiB
Matlab
function [...
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nextQuat, ... % quaternion state vector after fusion of measurements
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nextStates, ... % state vector after fusion of measurements
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nextP, ... % state covariance matrix after fusion of corrections
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innovation, ... % Declination innovation - rad
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varInnov] ... %
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= FuseMagnetometer( ...
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quat, ... % predicted quaternion states
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states, ... % predicted states
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P, ... % predicted covariance
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magData, ... % body frame magnetic flux measurements
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measDec, ... % magnetic field declination - azimuth angle measured from true north (rad)
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Tbn) % Estimated coordinate transformation matrix from body to NED frame
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q0 = quat(1);
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q1 = quat(2);
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q2 = quat(3);
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q3 = quat(4);
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magX = magData(1);
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magY = magData(2);
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magZ = magData(3);
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R_MAG = 0.1745^2;
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H = calcH_MAG(magX,magY,magZ,q0,q1,q2,q3);
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varInnov = (H*P*transpose(H) + R_MAG);
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Kfusion = (P*transpose(H))/varInnov;
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% Calculate the predicted magnetic declination
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magMeasNED = Tbn*[magX;magY;magZ];
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predDec = atan2(magMeasNED(2),magMeasNED(1));
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% Calculate the measurement innovation
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innovation = predDec - measDec;
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if (innovation > pi)
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innovation = innovation - 2*pi;
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elseif (innovation < -pi)
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innovation = innovation + 2*pi;
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end
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if (innovation > 0.5)
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innovation = 0.5;
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elseif (innovation < -0.5)
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innovation = -0.5;
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end
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% correct the state vector
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states(1:3) = 0;
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states = states - Kfusion * innovation;
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% the first 3 states represent the angular misalignment vector.
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% This is used to correct the estimate quaternion
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% Convert the error rotation vector to its equivalent quaternion
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% error = truth - estimate
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rotationMag = sqrt(states(1)^2 + states(2)^2 + states(3)^2);
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if rotationMag<1e-6
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deltaQuat = single([1;0;0;0]);
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else
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deltaQuat = [cos(0.5*rotationMag); [states(1);states(2);states(3)]/rotationMag*sin(0.5*rotationMag)];
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end
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% Update the quaternion states by rotating from the previous attitude through
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% the delta angle rotation quaternion
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nextQuat = [quat(1)*deltaQuat(1)-transpose(quat(2:4))*deltaQuat(2:4); quat(1)*deltaQuat(2:4) + deltaQuat(1)*quat(2:4) + cross(quat(2:4),deltaQuat(2:4))];
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% normalise the updated quaternion states
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quatMag = sqrt(nextQuat(1)^2 + nextQuat(2)^2 + nextQuat(3)^2 + nextQuat(4)^2);
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if (quatMag > 1e-6)
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nextQuat = nextQuat / quatMag;
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end
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% correct the covariance P = P - K*H*P
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P = P - Kfusion*H*P;
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% Force symmetry on the covariance matrix to prevent ill-conditioning
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% of the matrix which would cause the filter to blow-up
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P = 0.5*(P + transpose(P));
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% ensure diagonals are positive
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for i=1:9
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if P(i,i) < 0
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P(i,i) = 0;
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end
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end
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% Set default output for states and covariance
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nextP = P;
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nextStates = states;
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end |