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create Welford mean Vector with covariance and improve precision with Kahan summation (#20676)

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- WelfordMeanVector now computes covariance
 - use Kahan summation for Welford mean (but continue using float32 for actual mean, etc)
 - WelfordMean and WelfordMeanVector handle initial value and count roll over
 - Welford mean count rollover at 16 bit max to prevent numerical issues and shift weight to newer samples
 - sensors/vehicle_imu: update Welford mean usage (now simplified with resets removed)
    - fix vehicle_imu_status accel var, now properly rotated with full covariance matrix
 - gyro_calibration: update Welford mean usage
This commit is contained in:
Daniel Agar
2022-11-30 14:50:13 -05:00
committed by GitHub
parent 5155346d60
commit 89b81b0bd6
9 changed files with 527 additions and 248 deletions
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src/modules/gyro_calibration/GyroCalibration.hpp
+11 -4
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@@ -39,7 +39,7 @@
#include <px4_platform_common/posix.h>
#include <px4_platform_common/px4_work_queue/ScheduledWorkItem.hpp>
#include <drivers/drv_hrt.h>
#include <lib/mathlib/math/WelfordMean.hpp>
#include <lib/mathlib/math/WelfordMeanVector.hpp>
#include <lib/perf/perf_counter.h>
#include <lib/sensor_calibration/Gyroscope.hpp>
#include <uORB/Subscription.hpp>
@@ -79,11 +79,17 @@ private:
void Reset()
{
for (auto &m : _gyro_mean) {
m.reset();
for (int gyro = 0; gyro < MAX_SENSORS; gyro++) {
_gyro_mean[gyro].reset();
_gyro_last_update[gyro] = 0;
}
_last_calibration_update = hrt_absolute_time();
}
// return the square of two floating point numbers
static constexpr float sq(float var) { return var * var; }
uORB::SubscriptionInterval _parameter_update_sub{ORB_ID(parameter_update), 1_s};
uORB::Subscription _vehicle_status_sub{ORB_ID::vehicle_status};
@@ -91,7 +97,8 @@ private:
uORB::SubscriptionMultiArray<sensor_gyro_s, MAX_SENSORS> _sensor_gyro_subs{ORB_ID::sensor_gyro};
calibration::Gyroscope _gyro_calibration[MAX_SENSORS] {};
math::WelfordMean<float, 3> _gyro_mean[MAX_SENSORS] {};
math::WelfordMeanVector<float, 3> _gyro_mean[MAX_SENSORS] {};
matrix::Vector3f _gyro_cal_variance[MAX_SENSORS] {};
float _temperature[MAX_SENSORS] {};
hrt_abstime _gyro_last_update[MAX_SENSORS] {};