Kalman-Filter

Kalman-Filter from Linus Helgesson More...

Files
file	kalman.h
	Kalman-Filter Header.
file	kalman.c
	Kalman-Filter Implementation.

Data Structures
struct	Kalman
	Kalman-Filter State data. More...

Functions
void	kalmanInnovate (Kalman *data, double z1, double z2)
	Step the Kalman Filter. More...
void	kalmanInit (Kalman *data)
	Initialize a Kalman-State. More...

Detailed Description

Kalman-Filter from Linus Helgesson

Function Documentation

void kalmanInit

(

Kalman *

data

)

Initialize a Kalman-State.

Parameters

data	Kalman-State to be initialized

Definition at line 48 of file kalman.c.

References Kalman::p33, and Kalman::x3.

Referenced by orientationInit().

                              {
    data->x1 = 0.0f;
    data->x2 = 0.0f;
    data->x3 = 0.0f;

    // Init P to diagonal matrix with large values since
    // the initial state is not known
    data->p11 = 1000.0f;
    data->p12 = 0.0f;
    data->p13 = 0.0f;
    data->p21 = 0.0f;
    data->p22 = 1000.0f;
    data->p23 = 0.0f;
    data->p31 = 0.0f;
    data->p32 = 0.0f;
    data->p33 = 1000.0f;
}

void kalmanInnovate	(	Kalman *	data,
		double	z1,
		double	z2
	)

Step the Kalman Filter.

Parameters

data	Kalman-Filter State
z1	Angle from Accelerometer
z2	Corresponding Gyroscope data

Definition at line 66 of file kalman.c.

References DT, Kalman::p33, Q1, Q2, Q3, R1, R2, and Kalman::x3.

Referenced by orientationTask().

                                                        {
    double y1, y2;
    double a, b, c;
    double sDet;
    double s11, s12, s21, s22;
    double k11, k12, k21, k22, k31, k32;
    double p11, p12, p13, p21, p22, p23, p31, p32, p33;

    // Step 1
    // x(k) = Fx(k-1) + Bu + w:
    data->x1 = data->x1 + DT*data->x2 - DT*data->x3;
    //x2 = x2;
    //x3 = x3;

    // Step 2
    // P = FPF'+Q
    a = data->p11 + data->p21*DT - data->p31*DT;
    b = data->p12 + data->p22*DT - data->p32*DT;
    c = data->p13 + data->p23*DT - data->p33*DT;
    data->p11 = a + b*DT - c*DT + Q1;
    data->p12 = b;
    data->p13 = c;
    data->p21 = data->p21 + data->p22*DT - data->p23*DT;
    data->p22 = data->p22 + Q2;
    //p23 = p23;
    data->p31 = data->p31 + data->p32*DT - data->p33*DT;
    //p32 = p32;
    data->p33 = data->p33 + Q3;

    // Step 3
    // y = z(k) - Hx(k)
    y1 = z1-data->x1;
    y2 = z2-data->x2;

    // Step 4
    // S = HPT' + R
    s11 = data->p11 + R1;
    s12 = data->p12;
    s21 = data->p21;
    s22 = data->p22 + R2;

    // Step 5
    // K = PH*inv(S)
    sDet = 1/(s11*s22 - s12*s21);
    k11 = (data->p11*s22 - data->p12*s21)*sDet;
    k12 = (data->p12*s11 - data->p11*s12)*sDet;
    k21 = (data->p21*s22 - data->p22*s21)*sDet;
    k22 = (data->p22*s11 - data->p21*s12)*sDet;
    k31 = (data->p31*s22 - data->p32*s21)*sDet;
    k32 = (data->p32*s11 - data->p31*s12)*sDet;

    // Step 6
    // x = x + Ky
    data->x1 = data->x1 + k11*y1 + k12*y2;
    data->x2 = data->x2 + k21*y1 + k22*y2;
    data->x3 = data->x3 + k31*y1 + k32*y2;

    // Step 7
    // P = (I-KH)P
    p11 = data->p11*(1.0f - k11) - data->p21*k12;
    p12 = data->p12*(1.0f - k11) - data->p22*k12;
    p13 = data->p13*(1.0f - k11) - data->p23*k12;
    p21 = data->p21*(1.0f - k22) - data->p11*k21;
    p22 = data->p22*(1.0f - k22) - data->p12*k21;
    p23 = data->p23*(1.0f - k22) - data->p13*k21;
    p31 = data->p31 - data->p21*k32 - data->p11*k31;
    p32 = data->p32 - data->p22*k32 - data->p12*k31;
    p33 = data->p33 - data->p22*k32 - data->p13*k31;
    data->p11 = p11; data->p12 = p12; data->p13 = p13;
    data->p21 = p21; data->p22 = p22; data->p23 = p23;
    data->p31 = p31; data->p32 = p32; data->p33 = p33;
}