FFT Analysis of Sine Sweep
62 vues (au cours des 30 derniers jours)
Afficher commentaires plus anciens
David Kendal
le 23 Mai 2022
Commenté : Star Strider
le 24 Mai 2022
Hi there, I am trying to run FFT analysis of the sine sweep I have created and not sure if the graphs I'm producing are working as they should. I feel they look to smooth and wanted to see if I could do anything better. The code runs and works but I still feel there is something missing. Any help greatly appreciated.
Many thanks
T=5; %size of window
fs=44100; %sampling frequency
df=1/T; %frequency res
dt=1/fs; %time resolution
t=(0:+dt:T-dt); %time vector
df_t=500; %swept rate (Hz/seconds)
% pre-allocate size of t:
sweptsin = zeros(size(t));
for i=1:+1:length(t)
%i=i+1;
if(i==1) %initialise f and t.
f=20; ti=0;
else
ti=ti+dt; %time increment
f=f+df_t*dt; %freq increment
end
w=2*pi*f; %omega
sweptsin(i)=sin(w*ti); %swept sine wave
end
NFFT=1024; %NFFT-point DFT
X=fftshift(fft(sweptsin,NFFT)); %compute DFT using FFT
fVals1=(-NFFT/2:NFFT/2-1)/NFFT; %DFT Sample points
subplot(4,1,1)
plot(fVals1,abs(X));
title('Double Sided FFT - with FFTShift');
xlabel('Normalized Frequency')
ylabel('DFT Values');
L=length(sweptsin);
X=fft(sweptsin,NFFT);
Px=X.*conj(X)/(NFFT*L); %Power of each freq components
fVals2=fs*(0:NFFT/2-1)/NFFT;
subplot(4,1,2)
plot(fVals2,Px(1:NFFT/2),'b','LineSmoothing','on','LineWidth',1);
title('One Sided Power Spectral Density');
xlabel('Frequency (Hz)')
ylabel('PSD');
X=fft(sweptsin,NFFT); %compute DFT using FFT
nVals=(0:NFFT-1)/NFFT; %Normalized DFT Sample points
subplot(4,1,3)
plot(nVals,abs(X));
title('Double Sided FFT - without FFTShift');
xlabel('Normalized Frequency')
ylabel('DFT Values');
NFFT=1024;
L=length(sweptsin);
X=fftshift(fft(sweptsin,NFFT));
Px=X.*conj(X)/(NFFT*L); %Power of each freq components
fVals3=fs*(-NFFT/2:NFFT/2-1)/NFFT;
subplot(4,1,4)
plot(fVals3,10*log10(Px),'b');
title('Power Spectral Density');
xlabel('Frequency (Hz)')
ylabel('Power');
0 commentaires
Réponse acceptée
Star Strider
le 23 Mai 2022
Your posted code is likely as good as it is possible to get.
T=5; %size of window
fs=44100; %sampling frequency
df=1/T; %frequency res
dt=1/fs; %time resolution
t=(0:+dt:T-dt); %time vector
df_t=500; %swept rate (Hz/seconds)
% pre-allocate size of t:
sweptsin = zeros(size(t));
for i=1:+1:length(t)
%i=i+1;
if(i==1) %initialise f and t.
f=20; ti=0;
else
ti=ti+dt; %time increment
f=f+df_t*dt; %freq increment
end
w=2*pi*f; %omega
sweptsin(i)=sin(w*ti); %swept sine wave
end
NFFT=1024; %NFFT-point DFT
X=fftshift(fft(sweptsin,NFFT)); %compute DFT using FFT
fVals1=(-NFFT/2:NFFT/2-1)/NFFT; %DFT Sample points
subplot(4,1,1)
plot(fVals1,abs(X));
title('Double Sided FFT - with FFTShift');
xlabel('Normalized Frequency')
ylabel('DFT Values');
L=length(sweptsin);
X=fft(sweptsin,NFFT);
Px=X.*conj(X)/(NFFT*L); %Power of each freq components
fVals2=fs*(0:NFFT/2-1)/NFFT;
subplot(4,1,2)
plot(fVals2,Px(1:NFFT/2),'b','LineSmoothing','on','LineWidth',1);
title('One Sided Power Spectral Density');
xlabel('Frequency (Hz)')
ylabel('PSD');
X=fft(sweptsin,NFFT); %compute DFT using FFT
nVals=(0:NFFT-1)/NFFT; %Normalized DFT Sample points
subplot(4,1,3)
plot(nVals,abs(X));
title('Double Sided FFT - without FFTShift');
xlabel('Normalized Frequency')
ylabel('DFT Values');
NFFT=1024;
L=length(sweptsin);
X=fftshift(fft(sweptsin,NFFT));
Px=X.*conj(X)/(NFFT*L); %Power of each freq components
fVals3=fs*(-NFFT/2:NFFT/2-1)/NFFT;
subplot(4,1,4)
plot(fVals3,10*log10(Px),'b');
title('Power Spectral Density');
xlabel('Frequency (Hz)')
ylabel('Power');
figure
pspectrum(sweptsin,t,'spectrogram')
colormap(turbo)
.
4 commentaires
Star Strider
le 24 Mai 2022
They may be calculated differently, however I doubt that hte actual values are much different.
Plus de réponses (0)
Voir également
Catégories
En savoir plus sur Spectral Measurements dans Help Center et File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!