Your filtering approach is incorrect.
Try this:
load('H.mat');
time=H(:,1);
field=H(:,2);
n = length(time);
Ts = mean(diff(time));
Fs = 1/Ts;
Fn = Fs/2;
nfft = 2^nextpow2(n);
ft = fft(field,nfft)/n;
Fv = linspace(0, 1, fix(n/2)+1)*Fn; % Frequency Vector
Iv = 1:length(Fv); % Index Vector
figure(1)
subplot(3,1,1)
plot(time, field,'k.-')
xticks(2000:2016)
title('Initial field')
grid
subplot(3,1,2)
plot(Fv, abs(ft(Iv))*2)
title('Fourier spectrum. I need to filter out f=0.002 and higher ones')
grid
Wp = 0.0020/Fn; % Passband Frequency Vector (Normalised)
Ws = 0.0019/Fn; % Stopband Frequency Vector (Normalised)
Rp = 1; % Passband Ripple (dB)
Rs = 50; % Stopband Attenuation (dB)
[n,Wp] = ellipord(Wp,Ws,Rp,Rs); % Calculate Filter Order
[z,p,k] = ellip(n,Rp,Rs,Wp); % Default Here Is A Lowpass Filter
[sos,g] = zp2sos(z,p,k); % Use Second-Order-Section Implementation For Stability
field_output = filtfilt(sos,g,field); % Filter Signal (Here: ‘field’)
subplot(3,1,3)
plot(time, field_output)
title('Field Filtered')
grid on
figure(2)
freqz(sos, 2^14, Fs) % Bode Plot Of Filter
% set(subplot(2,1,1), 'XLim',[0 15]) % Optional, Change Limits As Necessary
% set(subplot(2,1,2), 'XLim',[0 15]) % Optional, Change Limits As Necessary
You may need to experiment with the filter passband if you want a different result. That should not be difficult.
