pd_swerling5.m

《Radar Systems Analysis and Design Using MatLab》

function pd = pd_swerling5 (input1, indicator, np, snrbar)
% This function is used to calculate the probability of 
% for Swerling 5 or 0 targets for np>1.
if(np == 1)
   'Stop, np must be greater than 1'
   return
end
format long
snrbar = 10.0^(snrbar/10.);
eps = 0.00000001;
delmax = .00001;
delta =10000.;
% Calculate the threshold Vt
if (indicator ~=1)
   nfa = input1;
   pfa =  np * log(2) / nfa;
else
   pfa = input1;
   nfa = np * log(2) / pfa;
end
sqrtpfa = sqrt(-log10(pfa));
sqrtnp = sqrt(np); 
vt0 = np - sqrtnp + 2.3 * sqrtpfa * (sqrtpfa + sqrtnp - 1.0);
vt = vt0;
while (abs(delta) >= vt0)
   igf = incomplete_gamma(vt0,np);
   num = 0.5^(np/nfa) - igf;
   temp = (np-1) * log(vt0+eps) - vt0 - factor(np-1);
   deno = exp(temp);
   vt = vt0 + (num / (deno+eps));
   delta = abs(vt - vt0) * 10000.0; 
   vt0 = vt;
end
% Calculate the Gram-Chrlier coeffcients
temp1 = 2.0 * snrbar + 1.0;
omegabar = sqrt(np * temp1);
c3 = -(snrbar + 1.0 / 3.0) / (sqrt(np) * temp1^1.5);
c4 = (snrbar + 0.25) / (np * temp1^2.);
c6 = c3 * c3 /2.0;
V = (vt - np * (1.0 + snrbar)) / omegabar;
Vsqr = V *V;
val1 = exp(-Vsqr / 2.0) / sqrt( 2.0 * pi);
val2 = c3 * (V^2 -1.0) + c4 * V * (3.0 - V^2) -...
   c6 * V * (V^4 - 10. * V^2 + 15.0);
q = 0.5 * erfc (V/sqrt(2.0));
pd =  q - val1 * val2;