leidaxitongfangzhen.m

MATLAB的程序

close  all;
clear  a11;
clc;
%%%%%%%产生雷达发射信号%%%%%%%%%%%%%%%%%%
code=[1,1,1,1,1,-1,-1,1,1,-1,1,-1,1];  %13位巴克码
tao=10e-6;%脉冲宽度10us
fc=28e6;%调频信号起始频率
f0=30e6;
fs=100e6;   %采样频率l00MHz
ts=1/fs;
B=4e6;%调频信号带宽
t_tao=0:1/fs:tao-1/fs;
N=length(t_tao);
k=B/fs*2*pi/max(t_tao);
n=length(code);
pha=0;
s=zeros(1,n*N);
for i=1:n;
    if code(i)==1
        pha=pi;
    else pha=0;
    end
    s(1,(i-1)*N+1:i*N)=cos(2*pi*fc*t_tao+k*cumsum(t_tao)+pha);
end
t=0:1/fs:13*tao-1/fs;
figure(1),subplot(2,1,1),plot(t,s),xlabel('t(单位:s)'),title('混合调制信号(13位巴克码+线性调频)');
s_fft_result=abs(fft(s(1:N)));
subplot(2,1,2),plot((0:fs/N:fs/2-fs/N),abs(s_fft_result(1:N/2))),xlabel('频率(单位:Hz)'),title('码内信号频谱');
%%%%%%%%%%%%%%%生脉冲压缩系数%%%%%%%%%%%%%%%
%___________正交解调_________________%
N=tao/ts;
n=0:N-1;
s1=s(1:N);
local_oscillator_i=cos(n*f0/fs*2*pi);%i路本振信号
local_oscillator_q=sin(n*f0/fs*2*pi);%q路本振信号
fbb_i=local_oscillator_i.*s1;%i路解调
fbb_q=local_oscillator_q.*s1;%q路解调
window=chebwin(51,40);
[b,a]=fir1(50, 2*B/fs,window);
fbb_i=[fbb_i,zeros(1,25)];
fbb_q=[fbb_q,zeros(1,25)];
fbb_i=filter(b,a,fbb_i);
fbb_q=filter(b,a,fbb_q);
fbb_i=fbb_i(26:end);%截取有效倍息
fbb_q=fbb_q(26:end);%截取有效信息
fbb=fbb_i+j*fbb_q;
%--------产生理想线性调频脉冲压缩匹配系数--------%
M=131072;%因为回波信号数据长度为3600点,所以利用FFT,做4096点FFT
D=B*tao;
match_filter_1=ts*fliplr(conj(fbb))*sqrt(D)*2/tao;
match_filter_1_fft=fft(match_filter_1,M);%第-次脉冲压缩处理匹配系数
figure(2),
subplot(2,1,1),plot(real(match_filter_1_fft)),title('脉冲压缩系数(实部)');
subplot(2,1,2),plot(imag(match_filter_1_fft)),title('脉冲压缩系数(虚部)');
N=length(s);
n=0:N-1;
local_oscillator_i=cos(n*f0/fs*2*pi);%i路本振信号
local_oscillator_q=sin(n*f0/fs*2*pi);%q路本振信号
fbb_i=local_oscillator_i.*s;%i路解调
fbb_q=local_oscillator_q.*s;%q路解调
window=chebwin(51,40);%这是采用50阶cheby窗的FIR低通滤波器
[b,a]=fir1(50, 0.5,window);
fbb_i=[fbb_i,zeros(1,25)];
fbb_q=[fbb_q,zeros(1,25)];
fbb_i=filter(b,a,fbb_i);
fbb_q=filter(b,a,fbb_q);
fbb_i=fbb_i(26:end);%截取有效倍息
fbb_q=fbb_q(26:end);%截取有效信息
signal=fbb_i+j*fbb_q;
clear fbb_i;
clear fbb_q;
signal_fft=fft(signal,M);
pc_result_fft=signal_fft.*match_filter_1_fft;
pc_result=ifft(pc_result_fft,M);
figure(3),plot((0:ts:length(signal)*ts-ts),pc_result(1:length(signal))), xlabel('时间,单位:s'),
title('回波脉冲压缩处理结果');
clear  local_oscillator_i;
clear  local_oscillator_q;
t=tao*length(code);
match_filter_2=2*ts*fliplr(conj(pc_result))*2/t;
match_filter_2_fft=fft(match_filter_2,M);%第二次脉冲压缩处理匹配系数
figure,
subplot(2,1,1),plot(real(match_filter_2_fft)),title('脉冲压缩系数（实部）');
subplot(2,1,2),plot(imag(match_filter_2_fft)),title('脉冲压缩系数（虚部）')
clear  fbb;
clear  match_fllter_1;
clear  match_filter_2;
clear  signal;
clear  signal_fft;
clear  pc_result;
clear  pc_result_fft;
%%%%%%%%%%%%%%%产生雷达回波%%%%%%%%%%%%%%%
f_frame=1e3;%雷达发射信号重频,单位Hz
T_frame=1/f_frame;
N_echo_frame=18;
f_doppler=3.5e3;%动目标的多普勒领串
t_frame=0:ts:T_frame-ts;
t_mobj=200e-6;%动目标位置
echo_mobj_pulse=[zeros(1,t_mobj/ts),s,zeros(1,(T_frame-t_mobj)/ts-length(s))];
echo_mobj=repmat(echo_mobj_pulse,1,N_echo_frame);
t_doppler=0:ts:N_echo_frame*T_frame-ts;
s_doppler=cos(2*pi*f_doppler*t_doppler);
s_echo_mobj=echo_mobj.*s_doppler;
t_fobj=450e-6;%固定目标位置
echo_fobj_pulse=[zeros(1,t_fobj/ts),s,zeros(1,(T_frame-t_fobj)/ts-length(s))];
s_echo_fobj=repmat(echo_fobj_pulse,1,N_echo_frame);
t_clutter=700e-6;%杂波位置
t_clutter_pulse=39e-6;
sigma=2;%瑞利分布canshu数sigma
t1=0:ts:t_clutter_pulse-ts;
rand('state',0);%把均匀分布伪随机发生器置为0状态
u=rand(1,length(t1));
echo_clutter=0.08*sqrt(2*log(1./u))*sigma;%,*s;
s_echo_clutter_pulse=[zeros(1,t_clutter/ts),echo_clutter,zeros(1,(T_frame-t_clutter)/ts-length(echo_clutter))];
s_echo_clutter=repmat(s_echo_clutter_pulse,1,N_echo_frame);
s_noise=0.1*rand(1,N_echo_frame*T_frame/ts);
s_echo=s_echo_mobj+s_echo_fobj+s_echo_clutter+s_noise;
clear s_echo_mobj;
clear s_echo_fobj;
clear s_echo_clultter;
clear s_echo_clutter_pulse;
clear s_noise;
clear echo_mobj_pulse;
clear echo_mobj;
clear echo_fobj_pulse;
clear echo_clutter;
clear s_doppler;
clear t_doppler;
%----------正交解调------%
N=N_echo_frame*T_frame/ts;
n=0:N-1;
local_oscillator_i=cos(n*f0/fs*pi);%I路本振信号
local_oscillator_q=sin(n*f0/fs*pi);%q路本振信号
s_echo_i=local_oscillator_i.*s_echo;%I路解调
s_echo_q=local_oscillator_q.*s_echo;%q路解调
window=chebwin(51,40);%这是采50阶cheby窗的FIR低通滤波器
[b,a]=fir1(50,2*B/fs,window);
s_echo_i=[s_echo_i,zeros(1,25)];
s_echo_q=[s_echo_q,zeros(1,25)];
s_echo_i=filter(b,a,s_echo_i);
s_echo_q=filter(b,a,s_echo_q);
s_echo_i=s_echo_i(26:end);%截取有效倍息
s_echo_q=s_echo_q(26:end);%截取有效信息
s_echo_mf=s_echo_i+j*s_echo_q;

clear s_echo;
clear local_oscillator_i;
clear local_oscillator_q;
clear s_echo_i;
clear s_eche_q;
clear n;
%%%%%%%%%%%%%%%%%%%%脉冲压缩处理%%%%%%%%%%%%%
for i=1:N_echo_frame
    s_echo_fft_result=fft(s_echo_mf(1,(i-1)*T_frame/ts+1:i*T_frame/ts),M);
    s_pc_fft_1=s_echo_fft_result.*match_filter_1_fft;
    s_pc_fft_2=s_pc_fft_1.*match_filter_2_fft;
    s_pc_result(i,:)=ifft(s_pc_fft_2,M);
end
clear s_echo_mf;
s_pc_result_1=s_pc_result';
s_pc_result_1=reshape(s_pc_result_1,1,N_echo_frame*M);
figure,subplot(2,1,1),plot(0:ts:length(s_pc_result_1)*ts-ts,real(s_pc_result_1)),
%N_echo_frame*T_frame-ts
xlabel('t(单位:s)'),title('脉冲压缩处理后结果(实部)');
subplot(2,1,2),plot(0:ts:length(s_pc_result_1)*ts-ts,imag(s_pc_result_1)),
xlabel('t(单位:s)'),title('脉冲压缩处理后结果(虚部)');
%%%%%%%%%%%%%%5固定杂波对消处理%%%%%%%%%%%%%%
for i=1:16
    s_MTI_result(i,:)=s_pc_result(i,:)+s_pc_result(i+2,:)-2*s_pc_result(i+1,:);
end
clear s_pc_result;
clear s_pc_result_1;
s_MTI_result_1=s_MTI_result';
s_MTI_result_1=reshape(s_MTI_result_1,1,(N_echo_frame-2)*M);
figure,subplot(2,1,1),plot(0:ts:length(s_MTI_result_1)*ts-ts,real(s_MTI_result_1)),
xlabel('t(单位:s)'),title('固定杂波对消后后结果(实部)');
subplot(2,1,2),plot(0:ts:length(s_MTI_result_1)*ts-ts,imag(s_MTI_result_1)),
xlabel('t(单位:s)'),title('固定杂波对消后后结果(虚部)');
clear s_MTI_result_1;
%%%%%%%%%%%%%%%%MTD处理和求模%%%%%%%%
%for i=1:T_frame/ts
 %   s_MTD_result_1(:,i)=fft(s_MTI_result(:,i),16);
 %end
%for i=1:T_frame/ts
%    s_MTD_result(i)=abs(s_MTD_result_1);
%end
%figure,plot(0:ts:N_echo_frame*T_frame-ts,s_MTD_result),
%xlabel('t(单位:s)'),title('MTD处理后求模结果（信号最大通道）');
for i=1:T_frame/ts
    s_MTD_result_1(:,i)=fft(s_MTI_result(:,i),16);
end
for i=1:T_frame/ts
    s_MTD_result(i)=abs(max(s_MTD_result_1(i)));
end
figure,plot(0:ts:T_frame-ts,s_MTD_result),
xlabel('t(单位:s)'),title('MTD处理后求模结果（信号最大通道）');
%%%%%%%%%CFAR处理%%%%%%%%%%%%%%%%%%%%%%%t
N=T_frame/ts;
cfar_result(1,1)=s_MTD_result(1,1)/(sqrt(2)/pi*mean(s_MTD_result(1,2:17)));
%第l点桓虚瞥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_MTD_result(1,1:i-1))+mean(s_MTD_result(1,i+1:i+16)))/2;
    cfar_result(1,i)=s_MTD_result(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点的噪声决定
    noise_mean=sqrt(2)/pi*max(mean(s_MTD_result(1,i-16:i-1)),mean(s_MTD_result(1,i+1:i+16)));
    cfar_result(1,i)=s_MTD_result(1,i)/noise_mean;
end
for k=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_MTD_result(1,k-16:k-1))+mean(s_MTD_result(1,k+1:N)))/2;
    cfar_result(1,k)=s_MTD_result(1,k)/noise_mean;
end
%最后1点的桓虚警处理的噪声均值由其前面l6点的噪声决定
    cfar_result(1,N)=s_MTD_result(1,N)/(sqrt(2)/pi*mean(s_MTD_result(1,N-16:N-1)));
figure,plot(0:ts:N*ts-ts,cfar_result),xlabel('t(单位:s)'),title('采用恒虚警处理处理结果');