# KalmanFilter C code error

Question asked by rabah.mohamed on Dec 30, 2016
Latest reply on Dec 31, 2016 by rabah.mohamed

I am using stm32f discovery board. I am trying to fuse Acceleromoter and gyroscope using KF. And here is a code i included that suppose to do this.

``#ifndef _Kalman_h#define _Kalman_hstruct Kalman {    /* Kalman filter variables */    double Q_angle; // Process noise variance for the accelerometer    double Q_bias; // Process noise variance for the gyro bias    double R_measure; // Measurement noise variance - this is actually the variance of the measurement noisedouble angle; // The angle calculated by the Kalman filter - part of the 2x1 state vectordouble bias; // The gyro bias calculated by the Kalman filter - part of the 2x1 state vectordouble rate; // Unbiased rate calculated from the rate and the calculated bias - you have to call getAngle to update the ratedouble P[2][2]; // Error covariance matrix - This is a 2x2 matrixdouble K[2]; // Kalman gain - This is a 2x1 vectordouble y; // Angle differencedouble S; // Estimate error};void   Init(struct Kalman* klm){    /* We will set the variables like so, these can also be tuned by the user */klm->Q_angle = 0.001;klm->Q_bias = 0.003;klm->R_measure = 0.03;klm->angle = 0; // Reset the angleklm->bias = 0; // Reset biasklm->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 - klm->P[0][1] = 0;klm->P[1][0] = 0;klm->P[1][1] = 0;}// The angle should be in degrees and the rate should be in degrees per second and the delta time in secondsdouble getAngle(struct Kalman * klm, double newAngle, double newRate, double dt) {    // Discrete Kalman filter time update equations - Time Update ("Predict")    // Update xhat - Project the state ahead    /* Step 1 */    klm->rate = newRate - klm->bias;    klm->angle += dt * klm->rate;    // Update estimation error covariance - Project the error covariance ahead    /* Step 2 */    klm->P[0][0] += dt * (dt*klm->P[1][1] - klm->P[0][1] - klm->P[1][0] + klm->Q_angle);    klm->P[0][1] -= dt * klm->P[1][1];    klm->P[1][0] -= dt * klm->P[1][1];    klm->P[1][1] += klm->Q_bias * dt;    // Discrete Kalman filter measurement update equations - Measurement Update ("Correct")    // Calculate Kalman gain - Compute the Kalman gain    /* Step 4 */    klm->S = klm->P[0][0] + klm->R_measure;    /* Step 5 */    klm->K[0] = klm->P[0][0] / klm->S;    klm->K[1] = klm->P[1][0] / klm->S;    // Calculate angle and bias - Update estimate with measurement zk (newAngle)    /* Step 3 */    klm->y = newAngle - klm->angle;    /* Step 6 */    klm->angle += klm->K[0] * klm->y;    klm->bias += klm->K[1] * klm->y;    // Calculate estimation error covariance - Update the error covariance    /* Step 7 */    klm->P[0][0] -= klm->K[0] * klm->P[0][0];    klm->P[0][1] -= klm->K[0] * klm->P[0][1];    klm->P[1][0] -= klm->K[1] * klm->P[0][0];    klm->P[1][1] -= klm->K[1] * klm->P[0][1];    return klm->angle;}void setAngle(struct Kalman* klm, double newAngle) { klm->angle = newAngle; } // Used to set angle, this should be set as the starting angledouble getRate(struct Kalman* klm) { return klm->rate; } // Return the unbiased rate/* These are used to tune the Kalman filter */void setQangle(struct Kalman* klm, double newQ_angle) { klm->Q_angle = newQ_angle; }void setQbias(struct Kalman* klm, double newQ_bias) { klm->Q_bias = newQ_bias; }void setRmeasure(struct Kalman* klm, double newR_measure) { klm->R_measure = newR_measure; }double getQangle(struct Kalman* klm) { return klm->Q_angle; }double getQbias(struct Kalman* klm) { return klm->Q_bias; }double getRmeasure(struct Kalman* klm) { return klm->R_measure; }#endif``

Now when using only the getAngle function, it always retunrs nan. i kept searching for the problem for 2 days until i found that whatever i do this function always returns a nan. So i will be glad if someone tell me what might be the problem.