# How to change the frequency values inside a time domain signal phase

• MATLAB
The problem I am having is simple. I have a Gaussian spectrum initially. Like this,

Process 1:

Matlab:
S = m0/sqrt(2*pi*sigma^2) * exp(-(vel_axis - mu).^2/(2*sigma^2));
Here, mu is the mean velocity (frequency) and sigma is the standard deviation. vel_axis is the axis on which I am calculating this Gaussian spectrum.

Then, with the help of random phase generators and using an inverse Fourier transform, I calculate the time domain signal of this spectrum.

Matlab:
s = ifft(fftshift(sqrt(N) .* sqrt(S) .* exp(1j .* Theta))); %timedomain
Here Theta is the uniform random phase between -pi to pi and N is the number of sampling points.

Process 2:

Now, I want to change the phase of the signal in the time domain to see the changes again in frequency domain.

Matlab:
s_modified_in_time_domain = abs(s) .* exp(1j .* unwrap(angle(sig)) .* (-1))
Here, I have multiplied (-1) so that I will have a spectrum around the value of -mu instead of mu. That is the idea. However, the spectrum is not around -mu and it is shifted to the positive axis of velocity (frequency). I have attached a plot to this post where it can be seen by the blue signal. The red signal is the actual time-domain signal of Process 1 in the frequency domain. And the Gaussian is around mu. Here mu is 5 [m/s].

Process 3:

Instead of doing the modification in the time domain, if I modify it in process 1 and in the equation of S, if I use -mu, instead of mu I get the desired result.

Therefore, I don't know why I get a shift in the plot of Process 2. Any idea if the equation for lower case s (equation number 2) does something weird?

In the plot: Blue is process 2 in the frequency domain Red is Process 1 with mu = 5 Yellow is Process 1 with mu = -5

The Blue plot should resemble the Yellow plot but it shifted towards the right. I want to do the change in the time domain and see the effect in the frequency domain. How can I use Process 2 in a good way. Just to show this effect I have used N as 4. So, it is very poorly sampled.

The code is done in MATLAB. This is just the idea. the code is lengthy with other things.