删除文件 arduino/Betas/RGB_V1.1.1/Kalman.cpp

arduino/Betas/RGB_V1.1.1/Kalman.cpp

@@ -1,93 +0,0 @@
-/* Copyright (C) 2012 Kristian Lauszus, TKJ Electronics. All rights reserved.
-
- This software may be distributed and modified under the terms of the GNU
- General Public License version 2 (GPL2) as published by the Free Software
- Foundation and appearing in the file GPL2.TXT included in the packaging of
- this file. Please note that GPL2 Section 2[b] requires that all works based
- on this software must also be made publicly available under the terms of
- the GPL2 ("Copyleft").
-
- Contact information
- -------------------
-
- Kristian Lauszus, TKJ Electronics
- Web      :  http://www.tkjelectronics.com
- e-mail   :  kristianl@tkjelectronics.com
- */
-
-#include "Kalman.h"
-
-Kalman::Kalman() {
-    /* We will set the variables like so, these can also be tuned by the user */
-    Q_angle = 0.001f;
-    Q_bias = 0.003f;
-    R_measure = 0.03f;
-
-    angle = 0.0f; // Reset the angle
-    bias = 0.0f; // Reset bias
-
-    P[0][0] = 0.0f; // Since we assume that the bias is 0 and we know the starting angle (use setAngle), the error covariance matrix is set like so - see: http://en.wikipedia.org/wiki/Kalman_filter#Example_application.2C_technical
-    P[0][1] = 0.0f;
-    P[1][0] = 0.0f;
-    P[1][1] = 0.0f;
-};
-
-// The angle should be in degrees and the rate should be in degrees per second and the delta time in seconds
-float Kalman::getAngle(float newAngle, float newRate, float dt) {
-    // KasBot V2  -  Kalman filter module - http://www.x-firm.com/?page_id=145
-    // Modified by Kristian Lauszus
-    // See my blog post for more information: http://blog.tkjelectronics.dk/2012/09/a-practical-approach-to-kalman-filter-and-how-to-implement-it
-
-    // Discrete Kalman filter time update equations - Time Update ("Predict")
-    // Update xhat - Project the state ahead
-    /* Step 1 */
-    rate = newRate - bias;
-    angle += dt * rate;
-
-    // Update estimation error covariance - Project the error covariance ahead
-    /* Step 2 */
-    P[0][0] += dt * (dt*P[1][1] - P[0][1] - P[1][0] + Q_angle);
-    P[0][1] -= dt * P[1][1];
-    P[1][0] -= dt * P[1][1];
-    P[1][1] += Q_bias * dt;
-
-    // Discrete Kalman filter measurement update equations - Measurement Update ("Correct")
-    // Calculate Kalman gain - Compute the Kalman gain
-    /* Step 4 */
-    float S = P[0][0] + R_measure; // Estimate error
-    /* Step 5 */
-    float K[2]; // Kalman gain - This is a 2x1 vector
-    K[0] = P[0][0] / S;
-    K[1] = P[1][0] / S;
-
-    // Calculate angle and bias - Update estimate with measurement zk (newAngle)
-    /* Step 3 */
-    float y = newAngle - angle; // Angle difference
-    /* Step 6 */
-    angle += K[0] * y;
-    bias += K[1] * y;
-
-    // Calculate estimation error covariance - Update the error covariance
-    /* Step 7 */
-    float P00_temp = P[0][0];
-    float P01_temp = P[0][1];
-
-    P[0][0] -= K[0] * P00_temp;
-    P[0][1] -= K[0] * P01_temp;
-    P[1][0] -= K[1] * P00_temp;
-    P[1][1] -= K[1] * P01_temp;
-
-    return angle;
-};
-
-void Kalman::setAngle(float angle) { this->angle = angle; }; // Used to set angle, this should be set as the starting angle
-float Kalman::getRate() { return this->rate; }; // Return the unbiased rate
-
-/* These are used to tune the Kalman filter */
-void Kalman::setQangle(float Q_angle) { this->Q_angle = Q_angle; };
-void Kalman::setQbias(float Q_bias) { this->Q_bias = Q_bias; };
-void Kalman::setRmeasure(float R_measure) { this->R_measure = R_measure; };
-
-float Kalman::getQangle() { return this->Q_angle; };
-float Kalman::getQbias() { return this->Q_bias; };
-float Kalman::getRmeasure() { return this->R_measure; };