ex9_14.m

matlab 7.x书上光盘所带的原代码,以及图象处理滤波的程序

clear all;
close all;
clc;
%%%%%%%%%%%产生瑞利噪声%%%%%%%%%%%%%%%%%%%%%%%
sigma=2;
t=1e-3;
fs=1e6;
ts=1/fs;
t1=0.05e-3:1/fs:0.2e-3-1/fs;
n=length(t1);
rand('state',0);
u=rand(1,n);
rayleigh_noise=sqrt(2*log2(1./u))*sigma;

%%%%%%%%%%%%产生目标回波%%%%%%%%%%%%%%%%%%%
N=t/ts;
s_pc_1=[zeros(1,100),1,zeros(1,N-101)];
noise=rand(1,N);
rayleigh_clutter=[zeros(1,50),rayleigh_noise,zeros(1,N-200)];
s_pc=s_pc_1+0.1*rayleigh_clutter+0.1*noise;
figure,plot((0:ts:t-ts),s_pc),
xlabel('t(单位:s)'),title('叠加了瑞利分布杂波、热噪声的目标回波');

%%%%%%%%%%%%%慢门限恒虚警处理%%%%%%%%%%%%%%%%%%%
 cfar_result=zeros(1,N);
 cfar_result(1,1)=s_pc(1,1);
 for i=2:N
     cfar_result(i)=s_pc(1,i)/mean(s_pc(1,1:i));
 end
 figure,plot((0:ts:t-ts),cfar_result),
xlabel('t(单位:s)'),title('采用慢门限处理结果');

%%%%%%%%%%%%%%%快门限恒虚警处理%%%%%%%%%%%%%
cfar_k_result=zeros(1,N);

cfar_k_result(1,1)=s_pc(1,1)/(sqrt(2)/pi*mean(s_pc(1,2:17)));
 
%第l点恒虚警处理时噪声均值由其后面的l6点的噪声决定
for i=2:16
%第2点到第16点的恒虚警处理的噪声均但由其前面和后面l6点的噪声共同决定
    noise_mean=sqrt(2)/pi*(mean(s_pc(1,1:i-1))+mean(s_pc(1,i+1:i+16)))/2;
    cfar_k_result(1,i)=s_pc(1,i)/noise_mean;
end
for i=17:N-17
%正常的数据点的恒虚警处理的噪声均值由其前面和后面各26点的噪声中的决定
    noise_mean=sqrt(2)/pi*max(mean(s_pc(1,i-16:i-1)),mean(s_pc(1,i+1:i+16)));
    cfar_k_result(1,i)=s_pc(1,i)/noise_mean;
end
for i=N-16:N-1
%例数第l6点到倒数第2点恒虚警处理的噪声均值由其前面16和后面的噪声共同决定
    noise_mean=sqrt(2)/pi*(mean(s_pc(1,i-16:i-1))+mean(s_pc(1,i+1:N)))/2;
    cfar_k_result(1,i)=s_pc(1,i)/noise_mean;
end
%最后-点的桓虚警处理的噪声均值由其前面l6点的噪声决定
cfar_k_result(1,N)=s_pc(1,N)/(sqrt(2)/pi*mean(s_pc(1,N-16:N-1)));
figure,plot(0:ts:t-ts,cfar_k_result),xlabel('t(单位:s)'),title('采用快门限恒虚警处理处理结果');