diff options
Diffstat (limited to 'apps/px4/attitude_estimator_bm/kalman.c')
-rw-r--r-- | apps/px4/attitude_estimator_bm/kalman.c | 115 |
1 files changed, 0 insertions, 115 deletions
diff --git a/apps/px4/attitude_estimator_bm/kalman.c b/apps/px4/attitude_estimator_bm/kalman.c deleted file mode 100644 index e4ea7a417..000000000 --- a/apps/px4/attitude_estimator_bm/kalman.c +++ /dev/null @@ -1,115 +0,0 @@ -/* - * kalman.c - * - * Created on: 01.12.2010 - * Author: Laurens Mackay - */ -#include "kalman.h" -//#include "mavlink_debug.h" - -void kalman_init(kalman_t *kalman, int states, int measurements, m_elem a[], - m_elem c[], m_elem gain_start[], m_elem gain[], m_elem x_apriori[], - m_elem x_aposteriori[], int gainfactorsteps) -{ - kalman->states = states; - kalman->measurements = measurements; - kalman->gainfactorsteps = gainfactorsteps; - kalman->gainfactor = 0; - - //Create all matrices that are persistent - kalman->a = matrix_create(states, states, a); - kalman->c = matrix_create(measurements, states, c); - kalman->gain_start = matrix_create(states, measurements, gain_start); - kalman->gain = matrix_create(states, measurements, gain); - kalman->x_apriori = matrix_create(states, 1, x_apriori); - kalman->x_aposteriori = matrix_create(states, 1, x_aposteriori); -} - -void kalman_predict(kalman_t *kalman) -{ - matrix_mult(kalman->a, kalman->x_aposteriori, kalman->x_apriori); -} - -void kalman_correct(kalman_t *kalman, m_elem measurement_a[], m_elem mask_a[]) -{ - //create matrices from inputs - matrix_t measurement = - matrix_create(kalman->measurements, 1, measurement_a); - matrix_t mask = matrix_create(kalman->measurements, 1, mask_a); - - //create temporary matrices - m_elem gain_start_part_a[KALMAN_MAX_STATES * KALMAN_MAX_MEASUREMENTS] = - { }; - matrix_t gain_start_part = matrix_create(kalman->states, - kalman->measurements, gain_start_part_a); - - m_elem gain_part_a[KALMAN_MAX_STATES * KALMAN_MAX_MEASUREMENTS] = - { }; - matrix_t gain_part = matrix_create(kalman->states, kalman->measurements, - gain_part_a); - - m_elem gain_sum_a[KALMAN_MAX_STATES * KALMAN_MAX_MEASUREMENTS] = - { }; - matrix_t gain_sum = matrix_create(kalman->states, kalman->measurements, - gain_sum_a); - - m_elem error_a[KALMAN_MAX_MEASUREMENTS * 1] = - { }; - matrix_t error = matrix_create(kalman->measurements, 1, error_a); - - m_elem measurement_estimate_a[KALMAN_MAX_MEASUREMENTS * 1] = - { }; - matrix_t measurement_estimate = matrix_create(kalman->measurements, 1, - measurement_estimate_a); - - m_elem x_update_a[KALMAN_MAX_STATES * 1] = - { }; - matrix_t x_update = matrix_create(kalman->states, 1, x_update_a); - - - - //x(:,i+1)=xapriori+(gainfactor*[M_50(:,1) M(:,2)]+(1-gainfactor)*M_start)*(z-C*xapriori); - - - //est=C*xapriori; - matrix_mult(kalman->c, kalman->x_apriori, measurement_estimate); - //error=(z-C*xapriori) = measurement-estimate - matrix_sub(measurement, measurement_estimate, error); - matrix_mult_element(error, mask, error); - - kalman->gainfactor = kalman->gainfactor * (1.0f - 1.0f - / kalman->gainfactorsteps) + 1.0f * 1.0f / kalman->gainfactorsteps; - - - - matrix_mult_scalar(kalman->gainfactor, kalman->gain, gain_part); - - matrix_mult_scalar(1.0f - kalman->gainfactor, kalman->gain_start, - gain_start_part); - - matrix_add(gain_start_part, gain_part, gain_sum); - - //gain*(z-C*xapriori) - matrix_mult(gain_sum, error, x_update); - - //xaposteriori = xapriori + update - - matrix_add(kalman->x_apriori, x_update, kalman->x_aposteriori); - - -// static int i=0; -// if(i++==4){ -// i=0; -// float_vect3 out_kal; -// out_kal.x = M(gain_sum,0,1); -//// out_kal_z.x = z_measurement[1]; -// out_kal.y = M(gain_sum,1,1); -// out_kal.z = M(gain_sum,2,1); -// debug_vect("out_kal", out_kal); -// } -} - -m_elem kalman_get_state(kalman_t *kalman, int state) -{ - return M(kalman->x_aposteriori, state, 0); -} |