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-rw-r--r--apps/px4/attitude_estimator_bm/kalman.c115
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);
-}