ardupilot/libraries/AP_NavEKF/EKFGSF_yaw.h

146 lines
7.3 KiB
C++

#pragma once
#pragma GCC optimize("O2")
#include <AP_NavEKF/AP_Nav_Common.h>
#include <AP_Math/AP_Math.h>
#include <AP_Math/vectorN.h>
#include <AP_Logger/LogStructure.h>
#define IMU_DT_MIN_SEC 0.001f // Minimum delta time between IMU samples (sec)
class EKFGSF_yaw
{
public:
// Constructor
EKFGSF_yaw();
// Update Filter States - this should be called whenever new IMU data is available
void update(const Vector3F &delAng,// IMU delta angle rotation vector measured in body frame (rad)
const Vector3F &delVel,// IMU delta velocity vector measured in body frame (m/s)
const ftype delAngDT, // time interval that delAng was integrated over (sec) - must be no less than IMU_DT_MIN_SEC
const ftype delVelDT, // time interval that delVel was integrated over (sec) - must be no less than IMU_DT_MIN_SEC
bool runEKF, // set to true when flying or movement suitable for yaw estimation
ftype TAS); // true airspeed used for centripetal accel compensation - set to 0 when not required.
// Fuse NE velocty mesurements and update the EKF's and GSF state and covariance estimates
// Should be called after update(...) whenever new velocity data is available
void fuseVelData(const Vector2F &vel, // NE velocity measurement (m/s)
const ftype velAcc); // 1-sigma accuracy of velocity measurement (m/s)
// set the gyro bias in rad/sec
void setGyroBias(Vector3f &gyroBias);
// get yaw estimated and corresponding variance return false if
// yaw estimation is inactive. n_clips will contain the number of
// models which were *not* used to create the yaw and yawVariance
// return values.
bool getYawData(ftype &yaw, ftype &yawVariance, uint8_t *n_clips=nullptr) const;
// get the length of the weighted average velocity innovation vector
// return false if not available
bool getVelInnovLength(ftype &velInnovLength) const;
// log EKFGSF data on behalf of an EKF caller. id0 and id1 are the
// IDs of the messages to log, e.g. LOG_NKY0_MSG, LOG_NKY1_MSG
void Log_Write(uint64_t time_us, LogMessages id0, LogMessages id1, uint8_t core_index);
private:
#if MATH_CHECK_INDEXES
typedef VectorN<ftype,2> Vector2;
typedef VectorN<ftype,3> Vector3;
typedef VectorN<VectorN<ftype,3>,3> Matrix3;
#else
typedef ftype Vector2[2];
typedef ftype Vector3[3];
typedef ftype Matrix3[3][3];
#endif
// Parameters
const ftype EKFGSF_gyroNoise{1.0e-1}; // yaw rate noise used for covariance prediction (rad/sec)
const ftype EKFGSF_accelNoise{2.0}; // horizontal accel noise used for covariance prediction (m/sec**2)
const ftype EKFGSF_tiltGain{0.2}; // gain from tilt error to gyro correction for complementary filter (1/sec)
const ftype EKFGSF_gyroBiasGain{0.04}; // gain applied to integral of gyro correction for complementary filter (1/sec)
const ftype EKFGSF_accelFiltRatio{10.0}; // ratio of time constant of AHRS tilt correction to time constant of first order LPF applied to accel data used by ahrs
// Declarations used by the bank of AHRS complementary filters that use IMU data augmented by true
// airspeed data when in fixed wing mode to estimate the quaternions that are used to rotate IMU data into a
// Front, Right, Yaw frame of reference.
Vector3F delta_angle;
Vector3F delta_velocity;
ftype angle_dt;
ftype velocity_dt;
struct ahrs_struct {
Matrix3F R; // matrix that rotates a vector from body to earth frame
Vector3F gyro_bias; // gyro bias learned and used by the quaternion calculation
bool aligned; // true when AHRS has been aligned
ftype accel_FR[2]; // front-right acceleration vector in a horizontal plane (m/s/s)
ftype vel_NE[2]; // NE velocity vector from last GPS measurement (m/s)
bool fuse_gps; // true when GPS should be fused on that frame
ftype accel_dt; // time step used when generating _simple_accel_FR data (sec)
};
ahrs_struct AHRS[N_MODELS_EKFGSF];
bool ahrs_tilt_aligned; // true the initial tilt alignment has been calculated
ftype accel_gain; // gain from accel vector tilt error to rate gyro correction used by AHRS calculation
Vector3F ahrs_accel; // filtered body frame specific force vector used by AHRS calculation (m/s/s)
ftype ahrs_accel_norm; // length of body frame specific force vector used by AHRS calculation (m/s/s)
ftype true_airspeed; // true airspeed used to correct for centripetal acceleratoin in coordinated turns (m/s)
// Runs quaternion prediction for the selected AHRS using IMU (and optionally true airspeed) data
void predictAHRS(const uint8_t mdl_idx);
// Applies a body frame delta angle to a body to earth frame rotation matrix using a small angle approximation
Matrix3F updateRotMat(const Matrix3F &R, const Vector3F &g) const;
// Initialises the tilt (roll and pitch) for all AHRS using IMU acceleration data
void alignTilt();
// Initialises the yaw angle for all AHRS using a uniform distribution of yaw angles between -180 and +180 deg
void alignYaw();
// The Following declarations are used by bank of EKF's that estimate yaw angle starting from a different yaw hypothesis for each filter.
struct EKF_struct {
ftype X[3]; // Vel North (m/s), Vel East (m/s), yaw (rad)
ftype P[3][3]; // covariance matrix
ftype S[2][2]; // N,E velocity innovation variance (m/s)^2
ftype innov[2]; // Velocity N,E innovation (m/s)
};
EKF_struct EKF[N_MODELS_EKFGSF];
bool vel_fuse_running; // true when the bank of EKF's has started fusing GPS velocity data
bool run_ekf_gsf; // true when operating condition is suitable for to run the GSF and EKF models and fuse velocity data
// Resets states and covariances for the EKF's and GSF including GSF weights, but not the AHRS complementary filters
void resetEKFGSF();
// Runs the state and covariance prediction for the selected EKF
void predict(const uint8_t mdl_idx);
// Runs the state and covariance update for the selected EKF using the GPS NE velocity measurement
// Returns false if the sttae and covariance correction failed
bool correct(const uint8_t mdl_idx, const Vector2F &vel, const ftype velObsVar);
// Forces symmetry on the covariance matrix for the selected EKF
void forceSymmetry(const uint8_t mdl_idx);
// The following declarations are used by the Gaussian Sum Filter that combines the state estimates from the bank of
// EKF's to form a single state estimate.
struct GSF_struct {
ftype yaw; // yaw (rad)
ftype yaw_variance; // Yaw state variance (rad^2)
ftype weights[N_MODELS_EKFGSF]; // Weighting applied to each EKF model. Sum of weights is unity.
};
GSF_struct GSF;
// Returns the probability for a selected model assuming a Gaussian error distribution
// Used by the Guassian Sum Filter to calculate the weightings when combining the outputs from the bank of EKF's
ftype gaussianDensity(const uint8_t mdl_idx) const;
// number of models whose weights underflowed due to excessive
// innovation variances:
uint8_t n_clips;
};