error_analisys.m File Reference

Functions
Ix Iy CIx CIy Rx Ry CRx CRy x y	norm (v) direction(v) Gpx Gvx Gpy Gvy Qx%Qy time_lenght
Plot Erro hold on	title ('Residue error')
Plot Erro hold on	xlabel ('Time(normalised)')
Plot Erro hold on	ylabel ('Error/mm') plot(t
Plot Erro hold on residue_x	plot (t, residue_y,'r') mean_residue_x
	legend (xL, yL,'Location','Best') figure
hold on	title ('Innovation error')
hold on innovation_x	plot (t, innovation_y,'r') mean_innovation_x
hold on	title ('Residue error covariance(window size 15)')
hold on	ylabel ('Covariance') plot(t
hold on cov_residue_x	plot (t, cov_residue_y,'r') legend('X'
hold on cov_residue_x Y hold on	title ('Innovation error covariance(window size 15)')
hold on cov_residue_x Y hold on cov_innovation_x	plot (t, cov_innovation_y,'r') legend('X'
hold on cov_residue_x Y hold on cov_innovation_x Y Plot process noise hold on	title ('Kalman process noise')
hold on cov_residue_x Y hold on cov_innovation_x Y Plot process noise hold on	ylabel ('noise/mm') plot(t
hold on cov_residue_x Y hold on cov_innovation_x Y Plot process noise hold on process_noise_x	plot (t, process_noise_y,'r') legend('X'
hold on cov_residue_x Y hold on cov_innovation_x Y Plot process noise hold on process_noise_x Y Plot gain position hold on	title ('Kalman Position Gain')
hold on cov_residue_x Y hold on cov_innovation_x Y Plot process noise hold on process_noise_x Y Plot gain position hold on	ylabel ('Gain') plot(t
hold on cov_residue_x Y hold on cov_innovation_x Y Plot process noise hold on process_noise_x Y Plot gain position hold on gain_position_x	plot (t, gain_position_y,'r') legend('X'
hold on cov_residue_x Y hold on cov_innovation_x Y Plot process noise hold on process_noise_x Y Plot gain position hold on gain_position_x Y hold on	title ('Kalman Velocity Gain')
hold on cov_residue_x Y hold on cov_innovation_x Y Plot process noise hold on process_noise_x Y Plot gain position hold on gain_position_x Y hold on gain_velocity_x	plot (t, gain_velocity_y,'r') legend('X'
hold on cov_residue_x Y hold on cov_innovation_x Y Plot process noise hold on process_noise_x Y Plot gain position hold on gain_position_x Y hold on gain_velocity_x Y Plot position and velocity hold on	title ('Object position')
hold on cov_residue_x Y hold on cov_innovation_x Y Plot process noise hold on process_noise_x Y Plot gain position hold on gain_position_x Y hold on gain_velocity_x Y Plot position and velocity hold on	ylabel ('Position/mm') plot(t
hold on cov_residue_x Y hold on cov_innovation_x Y Plot process noise hold on process_noise_x Y Plot gain position hold on gain_position_x Y hold on gain_velocity_x Y Plot position and velocity hold on position_x	plot (t, position_y,'r') legend('X'
hold on cov_residue_x Y hold on cov_innovation_x Y Plot process noise hold on process_noise_x Y Plot gain position hold on gain_position_x Y hold on gain_velocity_x Y Plot position and velocity hold on position_x Y hold on	title ('Object||velocity||')
hold on cov_residue_x Y hold on cov_innovation_x Y Plot process noise hold on process_noise_x Y Plot gain position hold on gain_position_x Y hold on gain_velocity_x Y Plot position and velocity hold on position_x Y hold on	ylabel ('Velocity/mm/s') plot(t
hold on cov_residue_x Y hold on cov_innovation_x Y Plot process noise hold on process_noise_x Y Plot gain position hold on gain_position_x Y hold on gain_velocity_x Y Plot position and velocity hold on position_x Y hold on velocity_module hold on	title ('Object velocity direction')
hold on cov_residue_x Y hold on cov_innovation_x Y Plot process noise hold on process_noise_x Y Plot gain position hold on gain_position_x Y hold on gain_velocity_x Y Plot position and velocity hold on position_x Y hold on velocity_module hold on	ylabel ('Direction/degrees') plot(t
Variables
Kalman performance estimation via residue and innovation error Read data clear	all
clc	E = dlmread('error_gain_pos_vel')
	start = 50
	innovation_x = E(start:start+time_lenght,1)
	innovation_y = E(start:start+time_lenght,2)
	cov_innovation_x = E(start:start+time_lenght,3)
	cov_innovation_y = E(start:start+time_lenght,4)
	residue_x = E(start:start+time_lenght,5)
	residue_y = E(start:start+time_lenght,6)
	cov_residue_x = E(start:start+time_lenght,7)
	cov_residue_y = E(start:start+time_lenght,8)
	position_x = E(start:start+time_lenght,9)
	position_y = E(start:start+time_lenght,10)
	velocity_module = E(start:start+time_lenght,11)
	velocity_angle = E(start:start+time_lenght,12)
	gain_position_x = E(start:start+time_lenght,13)
	gain_velocity_x = E(start:start+time_lenght,14)
	gain_position_y = E(start:start+time_lenght,15)
	gain_velocity_y = E(start:start+time_lenght,16)
	process_noise_x = E(start:start+time_lenght,17)
	process_noise_y = E(start:start+time_lenght,18)
	t = linspace(0,1,time_lenght+1)
Plot Erro	figure = ginput(1)
	std_residue_x = std(residue_x)
	mean_residue_y = mean(residue_y)
	std_residue_y = std(residue_y)
	xL = sprintf('X mean %g std %g',mean_residue_x,std_residue_x)
	yL = sprintf('Y mean %g std %g',mean_residue_y,std_residue_y)
	std_innovation_x = std(innovation_x)
	mean_innovation_y = mean(innovation_y)
	std_innovation_y = std(innovation_y)

---

Function Documentation

legend	(	xL	,
		yL	,
		'Location'	,
		'Best'
	)

Ix Iy CIx CIy Rx Ry CRx CRy x y norm

(

v

)

Referenced by calculate_traj_distance_to_atractor_pts(), calculate_traj_distance_to_repulsor_pts(), class_griddata::compute_grid(), and relocate_atractor_pts().

Here is the caller graph for this function:

hold on cov_residue_x Y hold on cov_innovation_x Y Plot process noise hold on process_noise_x Y Plot gain position hold on gain_position_x Y hold on gain_velocity_x Y Plot position and velocity hold on position_x plot	(	t	,
		position_y	,
		'r'
	)

hold on cov_residue_x Y hold on cov_innovation_x Y Plot process noise hold on process_noise_x Y Plot gain position hold on gain_position_x Y hold on gain_velocity_x plot	(	t	,
		gain_velocity_y	,
		'r'
	)

hold on cov_residue_x Y hold on cov_innovation_x Y Plot process noise hold on process_noise_x Y Plot gain position hold on gain_position_x plot	(	t	,
		gain_position_y	,
		'r'
	)

hold on cov_residue_x Y hold on cov_innovation_x Y Plot process noise hold on process_noise_x plot	(	t	,
		process_noise_y	,
		'r'
	)

hold on cov_residue_x Y hold on cov_innovation_x plot	(	t	,
		cov_innovation_y	,
		'r'
	)

hold on cov_residue_x plot	(	t	,
		cov_residue_y	,
		'r'
	)

hold on innovation_x plot	(	t	,
		innovation_y	,
		'r'
	)

Plot Erro hold on residue_x plot	(	t	,
		residue_y	,
		'r'
	)

hold on cov_residue_x Y hold on cov_innovation_x Y Plot process noise hold on process_noise_x Y Plot gain position hold on gain_position_x Y hold on gain_velocity_x Y Plot position and velocity hold on position_x Y hold on velocity_module hold on title

(

'Object velocity direction'

)

Type Constraints

hold on cov_residue_x Y hold on cov_innovation_x Y Plot process noise hold on process_noise_x Y Plot gain position hold on gain_position_x Y hold on gain_velocity_x Y Plot position and velocity hold on position_x Y hold on title

(

'Object||velocity||'

)

Type Constraints

hold on cov_residue_x Y hold on cov_innovation_x Y Plot process noise hold on process_noise_x Y Plot gain position hold on gain_position_x Y hold on gain_velocity_x Y Plot position and velocity hold on title

(

'Object position'

)

Type Constraints

hold on cov_residue_x Y hold on cov_innovation_x Y Plot process noise hold on process_noise_x Y Plot gain position hold on gain_position_x Y hold on title

(

'Kalman Velocity Gain'

)

Type Constraints

hold on cov_residue_x Y hold on cov_innovation_x Y Plot process noise hold on process_noise_x Y Plot gain position hold on title

(

'Kalman Position Gain'

)

Type Constraints

hold on cov_residue_x Y hold on cov_innovation_x Y Plot process noise hold on title

(

'Kalman process noise'

)

Type Constraints

hold on cov_residue_x Y hold on title

(

'Innovation error covariance(window size 15)'

)

Type Constraints

hold on title

(

'Residue error covariance(window size 15)'

)

hold on title

(

'Innovation error'

)

Plot Erro hold on title

(

'Residue error'

)

Type Constraints

hold on xlabel

(

'Time(normalised)'

)

hold on cov_residue_x Y hold on cov_innovation_x Y Plot process noise hold on process_noise_x Y Plot gain position hold on gain_position_x Y hold on gain_velocity_x Y Plot position and velocity hold on position_x Y hold on velocity_module hold on ylabel

(

'Direction/degrees'

)

hold on cov_residue_x Y hold on cov_innovation_x Y Plot process noise hold on process_noise_x Y Plot gain position hold on gain_position_x Y hold on gain_velocity_x Y Plot position and velocity hold on position_x Y hold on ylabel

(

'Velocity/mm/s'

)

hold on cov_residue_x Y hold on cov_innovation_x Y Plot process noise hold on process_noise_x Y Plot gain position hold on gain_position_x Y hold on gain_velocity_x Y Plot position and velocity hold on ylabel

(

'Position/mm'

)

hold on cov_residue_x Y hold on cov_innovation_x Y Plot process noise hold on process_noise_x Y Plot gain position hold on gain_position_x Y hold on ylabel

(

'Gain'

)

hold on cov_residue_x Y hold on cov_innovation_x Y Plot process noise hold on ylabel

(

'noise/mm'

)

Plot Error Covariance hold on cov_residue_x Y hold on ylabel

(

'Covariance'

)

hold on ylabel

(

'Error/mm'

)

---

Variable Documentation

close all

cov_innovation_x = E(start:start+time_lenght,3)

cov_innovation_y = E(start:start+time_lenght,4)

cov_residue_x = E(start:start+time_lenght,7)

cov_residue_y = E(start:start+time_lenght,8)

E = dlmread('error_gain_pos_vel')

end end figure = ginput(1)

gain_position_x = E(start:start+time_lenght,13)

gain_position_y = E(start:start+time_lenght,15)

gain_velocity_x = E(start:start+time_lenght,14)

gain_velocity_y = E(start:start+time_lenght,16)

innovation_x = E(start:start+time_lenght,1)

innovation_y = E(start:start+time_lenght,2)

mean_innovation_y = mean(innovation_y)

mean_residue_y = mean(residue_y)

position_x = E(start:start+time_lenght,9)

position_y = E(start:start+time_lenght,10)

process_noise_x = E(start:start+time_lenght,17)

process_noise_y = E(start:start+time_lenght,18)

residue_x = E(start:start+time_lenght,5)

residue_y = E(start:start+time_lenght,6)

start = 50

Referenced by DEVICE_read_data().

std_innovation_x = std(innovation_x)

std_innovation_y = std(innovation_y)

std_residue_x = std(residue_x)

std_residue_y = std(residue_y)

object t = linspace(0,1,time_lenght+1)

Referenced by calculate_freespace_lanemarkers(), calculate_freespace_laserobstacles(), check_haar_feature_tic(), detect_and_draw(), detect_and_draw_foveated(), interpolate_panandtilt(), logger::logger(), main(), ptucontrol_status_handler(), logger::ReadFormatsFromFile(), class_base_ipm::ReportImagesInProperties(), and search_for_new_target().

velocity_angle = E(start:start+time_lenght,12)

velocity_module = E(start:start+time_lenght,11)

xL = sprintf('X mean %g std %g',mean_residue_x,std_residue_x)

yL = sprintf('Y mean %g std %g',mean_residue_y,std_residue_y)