#pragma once #pragma GCC optimize("O2") #include #include #include #include #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 meassured in body frame (rad) const Vector3F &delVel,// IMU delta velocity vector meassured 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 Vector2; typedef VectorN Vector3; typedef VectorN,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; };