www.pudn.com > programradarsystemdisign.zip > fig3_8.m

% Use this program to reproduce Fig. 3.8 of text 
close all 
clear all 
eps = 0.000001; 
%Enter pulse width and bandwidth 
B = 200.0e6; %200 MHZ bandwidth 
T = 10.e-6; %10 micro second pulse; 
% Compute alpha 
mu = 2. * pi * B / T; 
% Determine sampling times 
delt = linspace(-T/2., T/2., 10001); % 1 nano sceond sampling interval 
% Compute the complex LFM representation 
Ichannal = cos(mu .* delt.^2 / 2.); % Real part 
Qchannal = sin(mu .* delt.^2 / 2.); % Imaginary Part 
LFM = Ichannal + sqrt(-1) .* Qchannal; % complex signal 
%Compute the FFT of the LFM waveform 
LFMFFT = fftshift(fft(LFM)); 
% Plot the real and Immaginary parts and the spectrum 
freqlimit = 0.5 / 1.e-9;% the sampling interval 1 nano-second 
freq = linspace(-freqlimit/1.e6,freqlimit/1.e6,10001); 
figure(1) 
plot(delt*1e6,Ichannal,'k'); 
axis([-1 1 -1 1]) 
grid 
xlabel('Time - microsecs') 
ylabel('Real part') 
title('T = 10 Microsecond, B = 200 MHz') 
figure(2) 
plot(delt*1e6,Qchannal,'k'); 
axis([-1 1 -1 1]) 
grid 
xlabel('Time - microsecs') 
ylabel('Imaginary part') 
title('T = 10 Microsecond, B = 200 MHz') 
figure(3) 
plot(freq, abs(LFMFFT),'k'); 
%axis tight 
grid 
xlabel('Frequency - MHz') 
ylabel('Amplitude spectrum') 
title('Spectrum for an LFM waveform and T = 10 Microsecond, B = 200 MHZ')