mirror of
https://gitee.com/mirrors_PX4/PX4-Autopilot.git
synced 2026-07-21 21:50:35 +08:00
EKF: Improve tilt alignment monitoring
Convert quaternion covariances into an angular alignment variance vector and discard the z component so that yaw uncertainty does not affect the result.
This commit is contained in:
+10
-5
@@ -49,11 +49,16 @@ void Ekf::controlFusionModes()
|
|||||||
// Get the magnetic declination
|
// Get the magnetic declination
|
||||||
calcMagDeclination();
|
calcMagDeclination();
|
||||||
|
|
||||||
// Once the angular uncertainty has reduced sufficiently, initialise the yaw and magnetic field states
|
// monitor the tilt alignment
|
||||||
float total_angle_variance = P[0][0] + P[1][1] + P[2][2] + P[3][3];
|
if (!_control_status.flags.tilt_align) {
|
||||||
if (total_angle_variance < 0.002f && !_control_status.flags.tilt_align) {
|
// whilst we are aligning the tilt, monitor the variances
|
||||||
_control_status.flags.tilt_align = true;
|
Vector3f angle_err_var_vec = calcRotVecVariances();
|
||||||
_control_status.flags.yaw_align = resetMagHeading(_mag_sample_delayed.mag);
|
|
||||||
|
// Once the tilt variances have reduced sufficiently, initialise the yaw and magnetic field states
|
||||||
|
if ((angle_err_var_vec(0) + angle_err_var_vec(1)) < 0.002f) {
|
||||||
|
_control_status.flags.tilt_align = true;
|
||||||
|
_control_status.flags.yaw_align = resetMagHeading(_mag_sample_delayed.mag);
|
||||||
|
}
|
||||||
}
|
}
|
||||||
|
|
||||||
// control use of various external souces for positon and velocity aiding
|
// control use of various external souces for positon and velocity aiding
|
||||||
|
|||||||
@@ -363,4 +363,7 @@ private:
|
|||||||
// calculate the measurement variance for the optical flow sensor
|
// calculate the measurement variance for the optical flow sensor
|
||||||
float calcOptFlowMeasVar();
|
float calcOptFlowMeasVar();
|
||||||
|
|
||||||
|
// rotate quaternion covariances into variances for an equivalent rotation vector
|
||||||
|
Vector3f calcRotVecVariances();
|
||||||
|
|
||||||
};
|
};
|
||||||
|
|||||||
@@ -654,3 +654,42 @@ Matrix3f EstimatorInterface::quat_to_invrotmat(const Quaternion quat)
|
|||||||
|
|
||||||
return dcm;
|
return dcm;
|
||||||
}
|
}
|
||||||
|
|
||||||
|
// calculate the variances for the rotation vector equivalent
|
||||||
|
Vector3f Ekf::calcRotVecVariances()
|
||||||
|
{
|
||||||
|
Vector3f rot_var_vec;
|
||||||
|
float q0,q1,q2,q3;
|
||||||
|
if (_state.quat_nominal(0) >= 0.0f) {
|
||||||
|
q0 = _state.quat_nominal(0);
|
||||||
|
q1 = _state.quat_nominal(1);
|
||||||
|
q2 = _state.quat_nominal(2);
|
||||||
|
q3 = _state.quat_nominal(3);
|
||||||
|
} else {
|
||||||
|
q0 = -_state.quat_nominal(0);
|
||||||
|
q1 = -_state.quat_nominal(1);
|
||||||
|
q2 = -_state.quat_nominal(2);
|
||||||
|
q3 = -_state.quat_nominal(3);
|
||||||
|
}
|
||||||
|
float t2 = q0*q0;
|
||||||
|
float t3 = acos(q0);
|
||||||
|
float t4 = -t2+1.0f;
|
||||||
|
float t5 = t2-1.0f;
|
||||||
|
float t6 = 1.0f/t5;
|
||||||
|
float t7 = q1*t6*2.0f;
|
||||||
|
float t8 = 1.0f/powf(t4,1.5f);
|
||||||
|
float t9 = q0*q1*t3*t8*2.0f;
|
||||||
|
float t10 = t7+t9;
|
||||||
|
float t11 = 1.0f/sqrtf(t4);
|
||||||
|
float t12 = q2*t6*2.0f;
|
||||||
|
float t13 = q0*q2*t3*t8*2.0f;
|
||||||
|
float t14 = t12+t13;
|
||||||
|
float t15 = q3*t6*2.0f;
|
||||||
|
float t16 = q0*q3*t3*t8*2.0f;
|
||||||
|
float t17 = t15+t16;
|
||||||
|
rot_var_vec(0) = t10*(P[0][0]*t10+P[1][0]*t3*t11*2.0f)+t3*t11*(P[0][1]*t10+P[1][1]*t3*t11*2.0f)*2.0f;
|
||||||
|
rot_var_vec(1) = t14*(P[0][0]*t14+P[2][0]*t3*t11*2.0f)+t3*t11*(P[0][2]*t14+P[2][2]*t3*t11*2.0f)*2.0f;
|
||||||
|
rot_var_vec(2) = t17*(P[0][0]*t17+P[3][0]*t3*t11*2.0f)+t3*t11*(P[0][3]*t17+P[3][3]*t3*t11*2.0f)*2.0f;
|
||||||
|
|
||||||
|
return rot_var_vec;
|
||||||
|
}
|
||||||
|
|||||||
Reference in New Issue
Block a user