📄 cr_covariance_detec.asv
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clc
total_len=100000;
L=16;
M=584;
Coff=48;
Po=0.01;
Fk=[-0.0253,-0.0342,-0.0358,-0.0167,0.0216,0.0649,0.0910,0.0819,0.0371,-0.0220,-0.0607,-0.0512,0.0079,0.0844,0.1269,0.0945,-0.0128,-0.1435,-0.2118,-0.1405,0.0946,0.4414,0.7859,1.0,1.0,0.7859,0.4414,0.0946,-0.1405,-0.2118,-0.1435,-0.0128,0.0945,0.1269,0.0844,0.0079,-0.0512,-0.0607,-0.0220,0.0371,0.0819,0.0910,0.0649,0.0216,-0.0167,-0.0358,-0.0342,-0.0253];
%求Hemiian matrix Q,H;
H=zeros(L,L+Coff-1);
for i5=1:L
for i6=1:Coff
H(i5,i6+i5-1)=Fk(i6);
end
end
G=zeros(L,L);
Q=zeros(L,L);
Qinv=zeros(L,L);
G=H*H';
Q=sqrt(G);
Qinv=inv(Q);
%计算门限比 r1
r1=(1+(L-1)*sqrt(2/(M*pi)))/(1+sqrt(2)*erfinv(1-2*(1-Po))*sqrt(2/M))
r1=L+M+1/M+2+erfinv(1-2*(1-Po)*sqrt(2/M))
%求矩阵X(n);
a=zeros(1,total_len);
for i=1:total_len
a(1,i)=simout(i);
end
% xn=zeros(1,M);
% for i1=1:M
% xn(1,i1)=a(1,i1);
% end
y=zeros(1,L);
for i2=1:L
for i3=1:M
y(1,i2)= y(1,i2)+a(1,i3)*a(1,i3+i2-1)';
end
end
Rx=zeros(L,L);
for i4=1:L
for i5=1:L
if i4==i5
Rx(i4,i5)=y(1,1);
else if i4<i5
Rx(i4,i5)=y(1,i5-i4+1);
else
Rx(i4,i5)=y(1,i4-i5+1)';
end
end
end
end
end
Rx=Rx/M;
% a=zeros(1,total_len);
% for i=1:total_len
% a(1,i)=simout(i);
% end
% xn=zeros(L,M);
%for j=0:999
% for i1=1:L
% for i2=1:M
% xn(i1,i2)=a(1,i1+i2-1);
% end
% end
% %求矩阵X(n)的协方差矩阵,Rx;
% xc=xn';
% Rx1=xn*xc;
% Rx=zeros(L,L);
% for i3=1:L
% for i4=1:L
% Rx(i3,i4)=norm(Rx1(i3,i4));
% end
% end
Rxn=Qinv*Rx*Qinv;
Tn1=0;
Tn2=0;
for i6=1:L
for i8=1:L
Tn1=Tn1+(norm(Rxn(i6,i8)))^2;
end
end
for i7=1:L
for i8=1:L
if abs(i7-i8)<1
Tn2=Tn2+(norm(Rxn(i7,i8)))^2;
end
end
end
k=Tn1/Tn2
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