QuadroCopter  0.1.4
Kalman Class Reference

#include <Kalman.h>

Public Member Functions

 Kalman ()
 
double getAngle (double newAngle, double newRate, double dt)
 
void setAngle (double newAngle)
 
double getRate ()
 
void setQangle (double newQ_angle)
 
void setQbias (double newQ_bias)
 
void setRmeasure (double newR_measure)
 
double getQangle ()
 
double getQbias ()
 
double getRmeasure ()
 

Constructor & Destructor Documentation

Kalman::Kalman ( )
inline
23  {
24  /* We will set the variables like so, these can also be tuned by the user */
25  Q_angle = 0.001;
26  Q_bias = 0.003;
27  R_measure = 0.03;
28 
29  angle = 0; // Reset the angle
30  bias = 0; // Reset bias
31 
32  P[0][0] = 0; // 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
33  P[0][1] = 0;
34  P[1][0] = 0;
35  P[1][1] = 0;
36  };

Member Function Documentation

double Kalman::getAngle ( double  newAngle,
double  newRate,
double  dt 
)
inline
38  {
39  // KasBot V2 - Kalman filter module - http://www.x-firm.com/?page_id=145
40  // Modified by Kristian Lauszus
41  // See my blog post for more information: http://blog.tkjelectronics.dk/2012/09/a-practical-approach-to-kalman-filter-and-how-to-implement-it
42 
43  // Discrete Kalman filter time update equations - Time Update ("Predict")
44  // Update xhat - Project the state ahead
45  /* Step 1 */
46  rate = newRate - bias;
47  angle += dt * rate;
48 
49  // Update estimation error covariance - Project the error covariance ahead
50  /* Step 2 */
51  P[0][0] += dt * (dt*P[1][1] - P[0][1] - P[1][0] + Q_angle);
52  P[0][1] -= dt * P[1][1];
53  P[1][0] -= dt * P[1][1];
54  P[1][1] += Q_bias * dt;
55 
56  // Discrete Kalman filter measurement update equations - Measurement Update ("Correct")
57  // Calculate Kalman gain - Compute the Kalman gain
58  /* Step 4 */
59  S = P[0][0] + R_measure;
60  /* Step 5 */
61  K[0] = P[0][0] / S;
62  K[1] = P[1][0] / S;
63 
64  // Calculate angle and bias - Update estimate with measurement zk (newAngle)
65  /* Step 3 */
66  y = newAngle - angle;
67  /* Step 6 */
68  angle += K[0] * y;
69  bias += K[1] * y;
70 
71  // Calculate estimation error covariance - Update the error covariance
72  /* Step 7 */
73  P[0][0] -= K[0] * P[0][0];
74  P[0][1] -= K[0] * P[0][1];
75  P[1][0] -= K[1] * P[0][0];
76  P[1][1] -= K[1] * P[0][1];
77 
78  return angle;
79  };
double Kalman::getQangle ( )
inline
88 { return Q_angle; };
double Kalman::getQbias ( )
inline
89 { return Q_bias; };
double Kalman::getRate ( )
inline
81 { return rate; }; // Return the unbiased rate
double Kalman::getRmeasure ( )
inline
90 { return R_measure; };
void Kalman::setAngle ( double  newAngle)
inline
80 { angle = newAngle; }; // Used to set angle, this should be set as the starting angle
void Kalman::setQangle ( double  newQ_angle)
inline
84 { Q_angle = newQ_angle; };
void Kalman::setQbias ( double  newQ_bias)
inline
85 { Q_bias = newQ_bias; };
void Kalman::setRmeasure ( double  newR_measure)
inline
86 { R_measure = newR_measure; };

The documentation for this class was generated from the following file: