mengtekaluo.zip_matlab_信号检测_噪声蒙特_检测性能仿真_检测性能曲线

%高斯白噪声下确知信号的检测(蒙特卡洛仿真) clc; clear all; close all; %LFM信号产生 M1 = 5000; %确定门限时仿真次数 M2 = 5000; %检测时蒙特卡洛次数 T = 20e-3; %LFM信号的脉宽20ms B = 20e3; %LFM信号的带宽20K k = B/T; %调频斜率 f0 = 100e3; %中心频率 Fs = 500e3; %采样频率 t = -T/2+1/Fs:1/Fs:T/2; %时间序列10000point s0 = 2*cos(2*pi*f0*t+pi*k*t.^2); %LFM信号序列 figure plot(t,s0); %LFM图像 xlabel('时间t'); ylabel('幅度V'); title('LFM信号图像'); SNR = -30:0.5:10; %信噪比 Pf = [5 1 0.1]/100; %虚警概率0.05 0.01 0.001 h_filter = fir1(5000,[0.36 0.44]); %带通滤波单位冲击响应函数 %蒙特卡洛仿真 tic; %计时开始 MAX_Baoluo = zeros(1,M2); %要保存最大值的矩阵 noise = zeros(M2,length(t)); %噪声矩阵 %确定门限仿真 for i = 1:M2 n0 = randn(1,length(s0)); %产生一段噪声 n0 = n0-mean(n0); %使均值为0 n0 = n0/std(n0); %使方差为1 n = filter(h_filter,1,n0); %带通滤波 noise(i,:) = n; %M2次仿真得到的噪声矩阵 s = n; %H0假设下的发送信号 m = 2*sqrt(B*T)*xcorr(s,s0)/length(s0); %自相关及对应纵坐标归化 Baoluo_Detection = abs(hilbert(m)); %取包络 MAX_Baoluo(i) = max(Baoluo_Detection); %最大值检测下，记录最大值 end %噪声归算 Power_n = 2*sum(noise(ceil(M2*rand),:).^2)/length(n0); %计算噪声功率值 Power_0 = Power_n*(10.^(SNR/10)); %计算对应信噪比下信号应具有的功率值 A0 = sqrt(Power_0/(sum(s0.^2)/length(s0))); %计算对应信噪比下信号应具有的幅度值 tmp = sort(MAX_Baoluo,'descend'); %M2次的最大值降序排列 VT = tmp(round(Pf.*M2)); %确定对应虚警概率下的门限值 pd_0050 = zeros(1,length(SNR)); %虚警概率5%下的检测概率矩阵 pd_0010 = zeros(1,length(SNR)); %虚警概率1%下的检测概率矩阵 pd_0001 = zeros(1,length(SNR)); %虚警概率0.1%下的检测概率矩阵 %检测时的蒙特卡洛仿真 j = 1; for snr = SNR %不同信噪比条件下 for i = 1:M1 %M1次仿真 n = noise(i,:); %读取记录的噪声 s = A0(j)*s0+n; %叠加信号，合成确定信噪比下的信号序列 m = 2*sqrt(B*T)*xcorr(s,s0)/length(s0); %自相关及对应纵坐标归化 Baoluo_Detection = abs(hilbert(m)); %取包络 Detection_max = max(Baoluo_Detection); %最大值检测下，记录最大值 %是否通过门限的判断是否检测到 if Detection_max > VT(1) pd_0050(j) = pd_0050(j)+1; %虚警概率5%下检测到+1 if Detection_max > VT(2) pd_0010(j) = pd_0010(j)+1; %虚警概率1%下检测到+1 if Detection_max > VT(3) pd_0001(j) = pd_0001(j)+1; %虚警概率0.1%下检测到+1 end end end end j = j+1; end %输出 pd_0050 = pd_0050/M1; %归算5%虚警概率下的检测概率 pd_0010 = pd_0010/M1; %归算1%虚警概率下的检测概率 pd_0001 = pd_0001/M1; %归算0.1%虚警概率下的检测概率 figure; plot(SNR,pd_0050,'r'); hold on; plot(SNR,pd_0010,'b'); hold on ; plot(SNR,pd_0001,'y'); xlabel('输入信噪比SNR(dB)'); ylabel('P_D'); title('ROC'); legend({'Pf = 5%','Pf = 1%','Pf = 0.1%'}); time = toc; %计时结束