Added .autosave to the controls .gitignore, updated the IMU analysis functions...

Added .autosave to the controls .gitignore, updated the IMU analysis functions and scripts for gyroscope, added a rough draft of a IMU model

controls/.gitignore

-*.asv
+*.asv
\ No newline at end of file
+*.autosave
\ No newline at end of file

controls/MATLAB/IMU/accelerometer_noise_analysis.m

@@ -14,6 +14,11 @@ gz = data.gz;
 % analyze the noise (deviation from mean) on each axis and compare the
 % emperical distribution to one generated from a quantized Gaussian
 % distrubtuion with the same variance. 
-quantized_accel_noise_gauss_anal( ax , 'x-axis')
-quantized_accel_noise_gauss_anal( ay , 'y-axis')
-quantized_accel_noise_gauss_anal( az , 'z-axis')
+quantized_noise_gauss_anal( ax , 'Accelerometer' , 'x-axis' , 'gs' )
+quantized_noise_gauss_anal( ay , 'Accelerometer' , 'y-axis', 'gs' )
+quantized_noise_gauss_anal( az , 'Accelerometer' , 'z-axis', 'gs' )
\ No newline at end of file
+
+
+quantized_noise_gauss_anal( gx , 'Gyroscope' , 'x-axis' , 'rad/s')
+quantized_noise_gauss_anal( gy , 'Gyroscope' , 'y-axis' , 'rad/s' )
+quantized_noise_gauss_anal( gz , 'Gyroscope' , 'z-axis' , 'rad/s' )
\ No newline at end of file

controls/MATLAB/IMU/microcart_imu_analysis_1.m

@@ -88,7 +88,7 @@ stem(bins,h);
 legend(['Quantized Gaussian Noise: N(0,',num2str(vx),')'],'Emperical Distribution')
 
 
-quantized_accel_noise_gauss_anal( ax )
+% quantized_accel_noise_gauss_anal( ax )
 
 
 

controls/MATLAB/IMU/quantized_accel_noise_gauss_anal.m → controls/MATLAB/IMU/quantized_noise_gauss_anal.m

-function varargout = quantized_accel_noise_gauss_anal( a , axis )
-% quantized_accel_noise_gauss_anal analysis for quantized acelerometer data 
+function varargout = quantized_noise_gauss_anal( a , sensor_name, axis , units )
+% quantized_noise_gauss_anal analysis for quantized sensor data 
 %
 %SYNTAX
-% quantized_accel_noise_gauss_anal( a , axis )
+% quantized_noise_gauss_anal(a , sensor_name, axis , units )
 % 
 %DESCRIPTION
 % ...to be written...
 %
 %
 %Inputs:
-%    a - vector of a single axis accelerometer reading 
-% axis - string specifying the axis label 
+%           a - vector of a single axis accelerometer reading 
+% sensor_name - string specifying the axis label 
+%        axis - string specifying the axis label 
+%       units - string specifying the physical units on that axis 
 %
 %Options:
 % none 
@@ -37,6 +39,10 @@ function varargout = quantized_accel_noise_gauss_anal( a , axis )
 % Initial bare bones function. 
 % - Matt Rich 11-15-2016
 %
+% Change funcdtion name and code to not specify what sensor it is for so it
+% can be used for any sensor producing quantized output
+% - Matt Rich 11-16-2016
+%
 
 mu = mean(a); 
 v = var(a); 
@@ -59,14 +65,14 @@ cgauss_left = normcdf(bins_left,mue,sigma);
 
 emp_dist = length(ea)*(cgauss_right-cgauss_left); 
 stairs(bins_left,emp_dist,'r','LineWidth',1) ; 
-xlabel('Error From Mean (gs)'); 
+xlabel(['Error From Mean (',units,')']); 
 ylabel('Occurences'); 
 grid; 
 hold on; 
 h = hist(ea,bins); 
 stem(bins,h); 
 legend(['Quantized Gaussian Noise: N(',num2str(mue),',',num2str(v),')'],'Emperical Distribution'); 
-title(['Accelerometer deviation from mean on ',axis]); 
+title([sensor_name,' deviation from mean on ',axis]); 
 
 
 end