#pragma once #pragma GCC optimize("O2") #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 float delAngDT, // time interval that delAng was integrated over (sec) - must be no less than IMU_DT_MIN_SEC const float 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 float TAS); // true airspeed used for centripetal accel compensation - set to 0 when not required. void pushVelData(Vector2f vel, // NE velocity measurement (m/s) float velAcc); // 1-sigma accuracy of velocity measurement (m/s) // get solution data for logging // return false if yaw estimation is inactive bool getLogData(float &yaw_composite, float &yaw_composite_variance, float yaw[N_MODELS_EKFGSF], float innov_VN[N_MODELS_EKFGSF], float innov_VE[N_MODELS_EKFGSF], float weight[N_MODELS_EKFGSF]); // get yaw estimated and corresponding variance // return false if yaw estimation is inactive bool getYawData(float &yaw, float &yawVariance); private: typedef float ftype; #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 float EKFGSF_gyroNoise{1.0e-1f}; // yaw rate noise used for covariance prediction (rad/sec) const float EKFGSF_accelNoise{2.0f}; // horizontal accel noise used for covariance prediction (m/sec**2) const float EKFGSF_tiltGain{0.2f}; // gain from tilt error to gyro correction for complementary filter (1/sec) const float EKFGSF_gyroBiasGain{0.04f}; // gain applied to integral of gyro correction for complementary filter (1/sec) const float EKFGSF_accelFiltRatio{10.0f}; // 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; float angle_dt; float 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{false}; // true when AHRS has been aligned float accel_FR[2]; // front-right acceleration vector in a horizontal plane (m/s/s) float vel_NE[2]; // NE velocity vector from last GPS measurement (m/s) bool fuse_gps; // true when GPS should be fused on that frame float 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 float 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) float ahrs_accel_norm; // length of body frame specific force vector used by AHRS calculation (m/s/s) bool ahrs_turn_comp_enabled; // true when compensation for centripetal acceleration in coordinated turns using true airspeed is being used. float 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); // 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 { float X[3]; // Vel North (m/s), Vel East (m/s), yaw (rad) float P[3][3]; // covariance matrix float S[2][2]; // N,E velocity innovation variance (m/s)^2 float 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 vel_data_updated; // true when velocity data has been updated bool run_ekf_gsf; // true when operating condition is suitable for to run the GSF and EKF models and fuse velocity data Vector2f vel_NE; // NE velocity observations (m/s) float vel_accuracy; // 1-sigma accuracy of velocity observations (m/s) // Initialises the EKF's and GSF states, but not the AHRS complementary filters void initialise(); // 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); // 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 { float yaw; // yaw (rad) float yaw_variance; // Yaw state variance (rad^2) float 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 float gaussianDensity(const uint8_t mdl_idx) const; };