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ekf2: refactor output predictor to class

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- refactor all EKF backend output predictor pieces into new OutputPredictor class
 - output states are now calculated immediately with new high rate IMU rather than after EKF update
 - IMU delayed sample is passed as around as control data to avoid storing an extra copy and make the requirement clear
This commit is contained in:
Daniel Agar
2023-01-18 10:59:34 -05:00
committed by GitHub
parent c054ca20cc
commit 95300d5637
39 changed files with 855 additions and 618 deletions
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src/modules/ekf2/EKF/mag_fusion.cpp
+3 -3
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@@ -215,7 +215,7 @@ bool Ekf::fuseMag(const Vector3f &mag, estimator_aid_source3d_s &aid_src_mag, bo
if (fused[0] && fused[1] && fused[2]) {
aid_src_mag.fused = true;
aid_src_mag.time_last_fuse = _imu_sample_delayed.time_us;
aid_src_mag.time_last_fuse = _time_delayed_us;
return true;
}
@@ -313,9 +313,9 @@ bool Ekf::fuseYaw(const float innovation, const float variance, estimator_aid_so
if (measurementUpdate(Kfusion, aid_src_status.innovation_variance, aid_src_status.innovation)) {
_time_last_heading_fuse = _imu_sample_delayed.time_us;
_time_last_heading_fuse = _time_delayed_us;
aid_src_status.time_last_fuse = _imu_sample_delayed.time_us;
aid_src_status.time_last_fuse = _time_delayed_us;
aid_src_status.fused = true;
_fault_status.flags.bad_hdg = false;