lab3_1(a).m

radar equation for target estimation

% c=20;
% seq=[-5,5,-5,-5,5,-5,5,-5,5,-5,5,5];
% for j=1:10;
%     L=seq(j);
%     for i=1:c
%         x((j-1)*20+i)=L
%     end;
% end;
% subplot(211);
% 
% %subplot(2,1,1);
% 
% %noise generation
% n=randn(c*10,1);
% plot(n);
% for i=1:c*10;
%     y(i)=x(i)+n(i);
% end;
% subplot(222);
% plot(y);
% 
% %matched filter
% for i=1:20
%     n(i)=pulse(c-i+1)
% end;
% %output of matched filter
% t=conv(y,h)*1/20
% subplot
% plot(t);
% 
% n1=randn(c*10,1)*200
% n2=randn(c*10,1)*0.3



%SIMULATION OF AWGN CHANNEL


%generating a rect. amplitude +/-5 pulse sequence
clear;
clf;
e=20;   %sample time
seq=[-5 5 -5 -5 5 -5 5 -5 5 5]; %pulse sequence
for j=1:10,
    L=seq(j);
    for i=1:e,
        x((j-1)*20+i)=L; %generating the pulse train
    end
end
%subplot(211);
%plot(seq);
subplot(411);
plot(x);
grid on;
ylim([-10 10]);
title('Original Signal');

%to generate unit variance gaussian noise 
%sequence of the same length 
%n=randn(e*10,1);
%n=randn(e*10,1)*200;
n=randn(e*10,1)*0.3%n=randn(e*10,1)*200;;
subplot(412);
plot(n);
grid on;
title('Additive White Gaussian Noise with unit variance');

%signal corrupted with white noise
for i=1:e*10,
    y(i)=x(i)+n(i);
end
subplot(413);
plot(y);
grid on;
title('Corrupted signal');

%SIMULATION OF MATCHED FILTER
for i=1:20,
    h(i)=pulse(e-i+1);
end
%output of matched filter t
t=conv(y,h)*1/20;
subplot(414);
plot(t);
grid on;