mirror of https://github.com/ArduPilot/ardupilot
136 lines
6.9 KiB
C++
136 lines
6.9 KiB
C++
#pragma once
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#pragma GCC optimize("O2")
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#include <AP_NavEKF/AP_Nav_Common.h>
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#include <AP_Math/AP_Math.h>
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#include <AP_Math/vectorN.h>
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#define IMU_DT_MIN_SEC 0.001f // Minimum delta time between IMU samples (sec)
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class EKFGSF_yaw
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{
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public:
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// Constructor
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EKFGSF_yaw();
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// Update Filter States - this should be called whenever new IMU data is available
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void update(const Vector3f &delAng,// IMU delta angle rotation vector meassured in body frame (rad)
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const Vector3f &delVel,// IMU delta velocity vector meassured in body frame (m/s)
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const float delAngDT, // time interval that delAng was integrated over (sec) - must be no less than IMU_DT_MIN_SEC
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const float delVelDT, // time interval that delVel was integrated over (sec) - must be no less than IMU_DT_MIN_SEC
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bool runEKF, // set to true when flying or movement suitable for yaw estimation
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float TAS); // true airspeed used for centripetal accel compensation - set to 0 when not required.
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// Fuse NE velocty mesurements and update the EKF's and GSF state and covariance estimates
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// Should be called after update(...) whenever new velocity data is available
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void fuseVelData(const Vector2f &vel, // NE velocity measurement (m/s)
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const float velAcc); // 1-sigma accuracy of velocity measurement (m/s)
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// set the gyro bias in rad/sec
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void setGyroBias(Vector3f &gyroBias);
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// get solution data for logging
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// return false if yaw estimation is inactive
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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]);
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// get yaw estimated and corresponding variance
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// return false if yaw estimation is inactive
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bool getYawData(float &yaw, float &yawVariance);
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private:
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typedef float ftype;
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#if MATH_CHECK_INDEXES
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typedef VectorN<ftype,2> Vector2;
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typedef VectorN<ftype,3> Vector3;
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typedef VectorN<VectorN<ftype,3>,3> Matrix3;
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#else
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typedef ftype Vector2[2];
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typedef ftype Vector3[3];
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typedef ftype Matrix3[3][3];
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#endif
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// Parameters
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const float EKFGSF_gyroNoise{1.0e-1f}; // yaw rate noise used for covariance prediction (rad/sec)
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const float EKFGSF_accelNoise{2.0f}; // horizontal accel noise used for covariance prediction (m/sec**2)
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const float EKFGSF_tiltGain{0.2f}; // gain from tilt error to gyro correction for complementary filter (1/sec)
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const float EKFGSF_gyroBiasGain{0.04f}; // gain applied to integral of gyro correction for complementary filter (1/sec)
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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
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// Declarations used by the bank of AHRS complementary filters that use IMU data augmented by true
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// airspeed data when in fixed wing mode to estimate the quaternions that are used to rotate IMU data into a
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// Front, Right, Yaw frame of reference.
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Vector3f delta_angle;
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Vector3f delta_velocity;
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float angle_dt;
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float velocity_dt;
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struct ahrs_struct {
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Matrix3f R; // matrix that rotates a vector from body to earth frame
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Vector3f gyro_bias; // gyro bias learned and used by the quaternion calculation
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bool aligned{false}; // true when AHRS has been aligned
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float accel_FR[2]; // front-right acceleration vector in a horizontal plane (m/s/s)
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float vel_NE[2]; // NE velocity vector from last GPS measurement (m/s)
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bool fuse_gps; // true when GPS should be fused on that frame
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float accel_dt; // time step used when generating _simple_accel_FR data (sec)
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};
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ahrs_struct AHRS[N_MODELS_EKFGSF];
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bool ahrs_tilt_aligned; // true the initial tilt alignment has been calculated
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float accel_gain; // gain from accel vector tilt error to rate gyro correction used by AHRS calculation
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Vector3f ahrs_accel; // filtered body frame specific force vector used by AHRS calculation (m/s/s)
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float ahrs_accel_norm; // length of body frame specific force vector used by AHRS calculation (m/s/s)
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float true_airspeed; // true airspeed used to correct for centripetal acceleratoin in coordinated turns (m/s)
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// Runs quaternion prediction for the selected AHRS using IMU (and optionally true airspeed) data
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void predictAHRS(const uint8_t mdl_idx);
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// Applies a body frame delta angle to a body to earth frame rotation matrix using a small angle approximation
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Matrix3f updateRotMat(const Matrix3f &R, const Vector3f &g);
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// Initialises the tilt (roll and pitch) for all AHRS using IMU acceleration data
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void alignTilt();
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// Initialises the yaw angle for all AHRS using a uniform distribution of yaw angles between -180 and +180 deg
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void alignYaw();
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// The Following declarations are used by bank of EKF's that estimate yaw angle starting from a different yaw hypothesis for each filter.
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struct EKF_struct {
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float X[3]; // Vel North (m/s), Vel East (m/s), yaw (rad)
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float P[3][3]; // covariance matrix
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float S[2][2]; // N,E velocity innovation variance (m/s)^2
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float innov[2]; // Velocity N,E innovation (m/s)
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};
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EKF_struct EKF[N_MODELS_EKFGSF];
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bool vel_fuse_running; // true when the bank of EKF's has started fusing GPS velocity data
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bool run_ekf_gsf; // true when operating condition is suitable for to run the GSF and EKF models and fuse velocity data
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// Resets states and covariances for the EKF's and GSF including GSF weights, but not the AHRS complementary filters
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void resetEKFGSF();
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// Runs the state and covariance prediction for the selected EKF
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void predict(const uint8_t mdl_idx);
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// Runs the state and covariance update for the selected EKF using the GPS NE velocity measurement
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// Returns false if the sttae and covariance correction failed
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bool correct(const uint8_t mdl_idx, const Vector2f &vel, const float velObsVar);
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// Forces symmetry on the covariance matrix for the selected EKF
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void forceSymmetry(const uint8_t mdl_idx);
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// The following declarations are used by the Gaussian Sum Filter that combines the state estimates from the bank of
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// EKF's to form a single state estimate.
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struct GSF_struct {
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float yaw; // yaw (rad)
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float yaw_variance; // Yaw state variance (rad^2)
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float weights[N_MODELS_EKFGSF]; // Weighting applied to each EKF model. Sum of weights is unity.
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};
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GSF_struct GSF;
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// Returns the probability for a selected model assuming a Gaussian error distribution
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// Used by the Guassian Sum Filter to calculate the weightings when combining the outputs from the bank of EKF's
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float gaussianDensity(const uint8_t mdl_idx) const;
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};
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