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