run_kalman_femur.cpp File Reference

File containing funtions to implement kalman filter on femur. More...

#include "postprocess.h"
#include <algorithm>

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Functions
int	run_kalman_femur (femur &fem, vector< vector< double > > wire_A_points, gsl_vector *tot_wire_len, vector< vector< double > > &state, vector< double > thetas)
	Run the EKF on the femur.

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Detailed Description

File containing funtions to implement kalman filter on femur.

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Function Documentation

int run_kalman_femur	(	femur &	fem,
		vector< vector< double > >	wire_A_points,
		gsl_vector *	tot_wire_len,
		vector< vector< double > > &	state,
		vector< double >	thetas
	)

Run the EKF on the femur.

Parameters:

[in]	fem	The femur structure with all data
[in]	wire_A_points	Base points of the active and passive wires connected to femur. (stored in the order as represented by the jacob equations) ie leftmost wire is labeled 1, irrespective of it being active or passive
[in]	tot_wire_len	Total wire lengths of the active wires, necessary for calculating measurement vector
[out]	state	The state vector, for each iteration. Output of the kalman filter

References tibia::accelerometers, tibia::active_wires, ekf_kalman_gain(), ekf_predict_step(), ekf_update_cov(), ekf_update_estimate(), generate_jacobian_femur(), generate_mes_vec_femur(), h_femur_encaps(), sensor::mdata, tibia::opti_count, tibia::optical, sensor::point_flag, set_initial_estimate(), set_proc_cov_mat(), and set_process_mat().

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