Introduction to Radar Basics - MATLAB Simulations for Radar Systems Design - page 56

nf = 6.0; %noise figure in dB
loss = 8.0; % radar losses in dB
range = linspace(5e3,125e3,1000); % range to target from 25 Km 165 Km,
1000 points
snr1 = radar_eq(pt, freq, g, sigmam, te, b, nf, loss, range);
snr2 = radar_eq(pt, freq, g, sigmaa, te, b, nf, loss, range);
% plot SNR versus range
figure(1)
rangekm = range ./ 1000;
plot(rangekm,snr1,'k',rangekm,snr2,'k:')
grid
legend('Misssile','Aircraft')
xlabel ('Detection range - Km');
ylabel ('SNR - dB');
Listing 1.12. MATLAB Program Ðfig1_27.mÑ
% Use this program to reproduce Fig. 1.27 of text.
close all
clear all
np = 7;
pt = 165.8e3; % peak power in Watts
freq = 3e+9; % radar operating frequency in Hz
g = 34.5139; % antenna gain in dB
sigmam = 0.5; % missile RCS m squared
sigmaa = 4; % aircraft RCS m squared
te = 290.0; % effective noise temperature in Kelvins
b = 1.0e+6; % radar operating bandwidth in Hz
nf = 6.0; %noise figure in dB
loss = 8.0; % radar losses in dB
% compute the single pulse SNR when 7-pulse NCI is used
SNR_1 = (10^1.3)/(2*7) + sqrt((((10^1.3)^2) / (4*7*7)) + ((10^1.3) / 7));
% compute the integration loss
LNCI = 10*log10((1+SNR_1)/SNR_1);
loss_total = loss + LNCI;
range = linspace(15e3,100e3,1000); % range to target from 15 to 100 Km,
1000 points
% modify pt by np*pt to account for pulse integration
snrmnci = radar_eq(np*pt, freq, g, sigmam, te, b, nf, loss_total, range);
snrm = radar_eq(pt, freq, g, sigmam, te, b, nf, loss, range);
snranci = radar_eq(np*pt, freq, g, sigmaa, te, b, nf, loss_total, range);
snra = radar_eq(pt, freq, g, sigmaa, te, b, nf, loss, range);
% plot SNR versus range
rangekm = range ./ 1000;