ekf2: always use corrected accel/gyro for filtered metrics

src/modules/ekf2/EKF/ekf_helper.cpp

@@ -870,17 +870,21 @@ void Ekf::updateIMUBiasInhibit(const imuSample &imu_delayed)
 	// inhibit learning of imu accel bias if the manoeuvre levels are too high to protect against the effect of sensor nonlinearities or bad accel data is detected
 	// xy accel bias learning is also disabled on ground as those states are poorly observable when perpendicular to the gravity vector
 	{
+		const Vector3f gyro_corrected = imu_delayed.delta_ang / imu_delayed.delta_ang_dt - _state.gyro_bias;
+
 		const float alpha = math::constrain((imu_delayed.delta_ang_dt / _params.acc_bias_learn_tc), 0.f, 1.f);
 		const float beta = 1.f - alpha;
-		_ang_rate_magnitude_filt = fmaxf(imu_delayed.delta_ang.norm() / imu_delayed.delta_ang_dt,
-						 beta * _ang_rate_magnitude_filt);
+
+		_ang_rate_magnitude_filt = fmaxf(gyro_corrected.norm(), beta * _ang_rate_magnitude_filt);
 	}
 
 	{
+		const Vector3f accel_corrected = imu_delayed.delta_vel / imu_delayed.delta_vel_dt - _state.accel_bias;
+
 		const float alpha = math::constrain((imu_delayed.delta_vel_dt / _params.acc_bias_learn_tc), 0.f, 1.f);
 		const float beta = 1.f - alpha;
 
-		_accel_magnitude_filt = fmaxf(imu_delayed.delta_vel.norm() / imu_delayed.delta_vel_dt, beta * _accel_magnitude_filt);
+		_accel_magnitude_filt = fmaxf(accel_corrected.norm(), beta * _accel_magnitude_filt);
 	}