雷达目标检测信号处理中恒虚警检测（CFAR）相关算法

%% 程序初始化 clc;clear all;close all; %% 均匀背景噪声（单目标&多目标） % shape=[200]; % variance=200; % noise_db=20; % noise_p=10.^(noise_db./10); % show_out=0; % [ xc ] = env_uniform(variance, shape, noise_db,show_out); % 单目标 % SNR1=15; signal1_p=10.^(SNR1./10).*noise_p; % xc(1,90)=signal1_p; % % 多目标 % SNR1=20;signal1_p=10.^(SNR1./10).*noise_p; % xc(1,90)=signal1_p; % SNR2=15;signal2_p=10.^(SNR2./10).*noise_p; % xc(1,102)=signal2_p; %% 杂波边缘背景噪声（单目标&多目标） shape=[100,200]; variance=200; noise_db=[20,30]; noise_p=10.^(noise_db./10); show_out=0; % [ xc ] = env_edge(variance, shape, noise_db, show_out); % 多目标 SNR1=15;signal1_p=10.^(SNR1./10).*noise_p(1,end); SNR2=12;signal2_p=10.^(SNR2./10).*noise_p(1,end); SNR3=8;signal3_p=10.^(SNR3./10).*noise_p(1,end); SNR4=5;signal4_p=10.^(SNR4./10).*noise_p(1,end); % loc1=randi([43,44],1,1); % xc(1,loc1)=signal1_p; % loc2=randi([46,48],1,1); % xc(1,loc2)=signal3_p; % loc3=randi([50,53],1,1); % xc(1,loc3)=signal2_p; % loc4=randi([55,58],1,1); % xc(1,loc4)=signal1_p; % loc5=randi([90,93],1,1); %接近杂波区，但是依然在 % xc(1,loc5)=signal1_p; % xc(1,loc5)=signal2_p; %这种杂波边缘有目标的情况，还需要优化 % xc(1,loc5)=signal3_p; % loc6=randi([102,108],1,1); % xc(1,loc6)=signal3_p; %% 迭代算法实现（杂波图） N=36; u=0.001; PAD=10^(-4); alpha=N.*(PAD.^(-1./N)-1); xtp=zeros(1,shape(end)); d0=0; d1=[0]; for i=1:1:4000 [ xc ] = env_edge(variance, shape, noise_db,show_out); loc1=randi([43,44],1,1); xc(1,loc1)=signal1_p; loc2=randi([46,48],1,1); xc(1,loc2)=signal3_p; loc3=randi([50,53],1,1); xc(1,loc3)=signal2_p; loc4=randi([55,58],1,1); xc(1,loc4)=signal1_p; loc6=randi([102,108],1,1); xc(1,loc6)=signal3_p; xtp=xtp.*(1-u)+xc.*u; d0=d0.*(1-u)+u; d1=cat(2,d1,d0); if mod(i,100)==0 %% 图谱显示 figure; plot(10.*log(abs(xc))./log(10)),hold on; plot(10.*log(abs(xtp.*alpha./d0))./log(10)),hold on; end end