72 lines
1.9 KiB
Matlab
72 lines
1.9 KiB
Matlab
%-OS-CFAR检测器均匀背景与杂波干扰目标背景下性能仿真-
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clc;
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clear all;
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N=32;
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r=3; %CMLD_CFAR检测器筛除掉r个较大的参考样本单元
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R=N-r; %参考单元长度
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n=N/2; %半滑窗长度
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k=3*N/4;
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T=16.2933; %标称系数
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Pfa=1e-6; %虚警概率
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syms T0
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g=Pfa-k*nchoosek(R,k)*gamma(R-k+1+T0)*gamma(k)/gamma(R+T0+1);
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x=solve(g);
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T0=double(x);
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M=1e4; %蒙特卡洛仿真次数
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SNR_dB=5:1:35; %信噪比
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SNR=10.^(SNR_dB./10);
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Simul_len=length(SNR); %仿真长度
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%OS-CFAR ideal%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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for i=1:Simul_len
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Pd(i)=OS_Pd_Fun(N,k,T,SNR(i));
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end
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plot(SNR_dB,Pd,'b');
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hold on
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%OS-CFAR simulation%%%%%%%%%%%%%%%%%%%%%%%%
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for i=1:Simul_len
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count=0;
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for j=1:M
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lambda=1; %产生噪声，长度为N
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u=rand(1,N);
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exp_noise=log(u)*(-lambda);
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lambda=SNR(i); %产生待检测单元
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u=rand(1,2);
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CUT=log(u(1))*(-lambda);
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exp_noise(N)=log(u(2))*(-lambda);
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exp_noise=sort(exp_noise);
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if(CUT>T*exp_noise(k))
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count=count+1;
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end
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end
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Pd_sim(i)=count/M;
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end
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plot(SNR_dB,Pd_sim,'-*r');
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hold on
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%%%%%%%%%%%%%%%CMLD_CFAR检测器筛除掉r个较大的参考样本单%%%%%%%%%%%%%%%%%%
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for i=1:Simul_len
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count=0;
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for j=1:M
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lambda=1; %产生噪声，长度为N-1
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u=rand(1,N-1);
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exp_noise(1:N-1)=log(u)*(-lambda);
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lambda=SNR(i); %产生待检测单元及一个干扰目标
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u=rand(1,2);
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CUT=log(u(1))*(-lambda);
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exp_noise(N)=log(u(2))*(-lambda);
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exp_noise=sort(exp_noise);
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exp_noise1(1:N-r)=exp_noise(1:N-r);
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if(CUT>T0*exp_noise1(k))
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count=count+1;
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end
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end
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Pd_sim_1(i)=count/M;
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end
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plot(SNR_dB,Pd_sim_1,'--g');
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hold on
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title('OS-CFAR 检测概率曲线,N=32,Pf=1e-6');
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xlabel('信噪比(dB)');ylabel('检测概率');
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legend('OS-ideal','OS-simulation','OS-1interference'); |