How can I find the Power spectral density of a filtered Noise?

I have this following code of generating noise and filtering it.. However I ailrd to plot its PSD of filtered Noise, as mentioned in coments?

N=2^10;

time=1:1:N;
time=time*1e-3;
time=time/N;
size(time)
bandwidth=100e3;
irn=10e-9;
plotting=1;
noisebw=(1/(max(time)/length(time)) )/2;

%%% SENSOR DATA
ws=(noisebw)/bandwidth; 
Wn=1/ws;  
[b,a] = butter(2,Wn,'low');

VN1=irn*sqrt(bandwidth); 
VN2=sqrt(ws);

noise1=VN1*randn(size(time));
noise2=filter(b,a,noise1);
noise3=VN2*noise2;   % filtered Noise
if plotting
    
    figure(100);
    
    plot(time,noise1,'-k','Linewidth',2);
    hold on;
        
    plot(time,noise2,'-y','Linewidth',2);
         
    plot(time,noise3,'-m','Linewidth',2);
    grid on;
    legend('noise high bw','filtered','noise low bw');
    title('noise source function outputs');
end

Answer 1

[Ameer Hamza]

This example show how to plot PSD using FFT: https://www.mathworks.com/help/signal/ug/power-spectral-density-estimates-using-fft.html