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EKF: Improve tilt alignment monitoring

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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:
Paul Riseborough
2016-05-17 11:17:24 +10:00
parent 6ca8a36782
commit 1540e937b1
3 changed files with 52 additions and 5 deletions
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EKF/ekf_helper.cpp
+39
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@@ -654,3 +654,42 @@ Matrix3f EstimatorInterface::quat_to_invrotmat(const Quaternion quat)
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;
}