How to keep main signal and suppress/remove other signal?

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clc
clf
close all
clear all
%%
%import spectrum
load('I_d.mat');
load('depth.mat');
Fs = 200*1e3; %sampling rate: 200 kHz
time = 1/Fs:1/Fs:0.006; %time interval (unit:s)
figure(1)
plot(time,I_d);
title('original signal');
xlabel('time (s)');
ylabel('Amplitude');
signal = I_d;
window = hanning(length(signal));
signal = signal.* window;
FFT = abs(fftshift(fft(signal,2048)));
FFT = FFT/max(FFT);
figure(2)
plot(depth,log(FFT),'linewidth',1);
title('after doing FFT')
xlabel('Depth (µm)');
ylabel('Amplitude');
set(gca,'linewidth',1,'fontsize',15);
grid on
%% plot spectrum with the other method
Fs = 2001e3; %sampling rate
time = 1/Fs:1/Fs:0.006; %time interval (unit:s)
%Default window is hamming window
figure(3)
pwelch(signal,[],[],[],Fs); %[] length of window to be used
The main signal is at the 2000µm depth (figure).
How do I suppress other signal besides this main signal and maintain signal to noise ratio?

Risposta accettata

Image Analyst
Image Analyst il 15 Feb 2022
That's not PSF (Point Spread Function). pwelch() computes PSD (Power Spectral Density). Basically you can fft the signal, then zero out all elements except those at or around 2000 and -2000, and then inverse transform.
  2 Commenti
Image Analyst
Image Analyst il 17 Feb 2022
Not sure why your x axis has units of depth (space domain) instead of Hz (frequency domain). Can you explain?
Vivian Yu
Vivian Yu il 25 Mar 2022
Thanks for your reply. Acturally, the depth information depends on frequency because of Wiener-Khinchin theorem. The difference of optical pass length between reference arm and sample arm causes time difference. This concept is based on swept-source optical coherence tomography.

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