Non-uniform Discrete Data Sample Filtering

9 views (last 30 days)
Hello,
I have collected some data from my encoder and IMU and I am trying to come up with a calibration function. However the data is quite noisy (especially IMU). I timestamped then numerized the timestamp using datenum function. I would like to have a spline like output.
I have come across this question and trying to utilize the code shared.
D = load('test_Data.mat');
t = D.test_data(:,1);
s = D.test_data(:,2);
Fs = 1; % Sampling Frequency
Ts = 1; % Sampling Interval
[sr,tr] = resample(s, t, Fs); % Resample, Return Resampled Signal & New Time Vector
sre = sr(1:end-2); % Eliminate End Transient
tre = tr(1:end-2); % Eliminate End Transient
figure
plot(t, s)
hold on
plot(tre, sre, '--')
hold off
grid
legend('Original Signal', 'Resampled Signal')
L = numel(t); % Signal Length
Fn = Fs/2; % Nyquist Frequency
sm = sre - mean(sre); % Subtract Mean
FTs = fft(sm)/L; % Scaled Fourier Transform
Fv = linspace(0, 1, fix(L/2)+1)*Fn; % Frequency Vector
Iv = 1:numel(Fv); % Index Vector
figure
plot(Fv, abs(FTs(Iv))*2)
grid
title('Fourier Transform')
Wp = [0.05]/Fn; % Passband Frequency (Normalised)
Ws = [0.09]/Fn; % Stopband Frequency (Normalised)
Rp = 1; % Passband Ripple
Rs = 60; % Passband Ripple (Attenuation)
[n,Wp] = ellipord(Wp,Ws,Rp,Rs); % Elliptic Order Calculation
[z,p,k] = ellip(n,Rp,Rs,Wp,'low'); % Elliptic Filter Design: Zero-Pole-Gain
[sos,g] = zp2sos(z,p,k); % Second-Order Section For Stability
figure
freqz(sos, 2^16, Fs) % Filter Bode Plot
sre_filt = filtfilt(sos, g, sre); % Filter Signal
figure
subplot(2,1,1)
plot(tre, sre)
grid
title('Resampled Signal')
subplot(2,1,2)
plot(tre, sre_filt, '-')
grid
title('Filtered Resampled Signal')
However resampling results singular, a single result; not an array.
  3 Comments
Kerem Asaf Tecirlioglu
Kerem Asaf Tecirlioglu on 24 Aug 2022
Edited: Kerem Asaf Tecirlioglu on 24 Aug 2022
I have handled the NaN value by replacing with the nearest integer sample. I am attaching the arrays .
a=1;
q=1;
for i = 1:size(TT1.imu_val)
if isnan(TT1.imu_val(i))
a = a + 1;
else
for x = q:i
TT1.imu_val(x) = TT1.imu_val(i);
end
a = 1;
q = 1 + x;
end
end
I have never used matlab for filtering before. How should I proceed with filtering
Mathieu NOE
Mathieu NOE on 24 Aug 2022
hi
for filtering look for example for smoothdata

Sign in to comment.

Answers (1)

Maximilian Schönau
Maximilian Schönau on 10 Oct 2022
I would reccomend you using the live script task "Smooth Data". There you can graphically try out different filter methods and after that convert your favorite filter to code.

Products


Release

R2022a

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!