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Telegram/Telegraph/AttitudeESKF.hpp
2016-02-25 01:03:51 +01:00

110 lines
3.3 KiB
C++

/*
* AttitudeESKF.hpp
*
* Copyright (c) 2013 Gareth Cross. All rights reserved.
*
* This file is part of kalman-ios.
*
* kalman-ios is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* kalman-ios is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with kalman-ios. If not, see <http://www.gnu.org/licenses/>.
*
* Created on: 12/24/2013
* Author: gareth
*/
#ifndef __AttitudeESKF__
#define __AttitudeESKF__
#include "quaternion.hpp"
#include "matrix.hpp"
/**
* @class AttitudeESKF
* @brief Implementation of an error-state EKF for attidude determination using Quaternions
* @note Two possible reference vectors (gravity and magnetic field) are used.
* @see 'Attitude Error Representations for Kalman Filtering' F. Landis Markley
*/
class AttitudeESKF
{
public:
/**
* @brief Ctor, initializes P,Q and R with identity matrices
*/
AttitudeESKF();
/**
* @brief Perform the prediction step
* @param wg Uncorrected gyroscope readings (fixed frame)
* @param dt Time step
*
* @note Integrates the nominal state using RK4.
*/
void predict(const matrix<3>& wg, float dt);
/**
* @brief Perform the update step
* @param ab Accelerometer readings
* @param mb Uncorrected magnetometer readings
* @param includeMag If true, magnetometer data is used in update step
*
* @note Without includeMag=true, no yaw corrections are possible.
*/
void update(const matrix<3>& ab, const matrix<3>& mb, bool includeMag);
/*
* Accessors for internal state variables
*/
const quat& getState() const { return m_q; } /** Orientation as quaternion */
bool isStable() const { return m_isStable; } /** False if the kalman gain is singular */
void setGyroBias(const matrix<3>& bias) { m_b = bias; } /** Steady-state bias of the gyroscope */
void setMagnetometerOffset(const matrix<3>& offset) { m_mc = offset; } /** Bias of the magnetic field */
void setInertialField(const matrix<3>& mi) { m_mi = mi; } /** Magnetic field in inertial frame */
matrix<3,3>& Q() { return m_Q; } /** Process covariance matrix */
matrix<6,6>& R() { return m_R; } /** Measurement covariance matrix */
const matrix<3>& getAPred() const { return m_aPred; } /** Predicted acceleration */
const matrix<3>& getMPred() const { return m_mPred; } /** Predicted magnetic field */
const matrix<3>& getMMeas() const { return m_mMeas; } /** Measured magnetic field, after normalization */
public:
quat m_q;
matrix<3> m_dx;
matrix<3> m_b;
matrix<3> m_mc;
matrix<3> m_mi;
matrix<3,3> m_P;
matrix<3,3> m_Q;
matrix<6,6> m_R;
bool m_isStable;
matrix<3> m_aPred;
matrix<3> m_mPred;
matrix<3> m_mMeas;
};
#endif /* defined(__AttitudeESKF__) */