lfm+13code.txt

13位巴克码+线形调频信号

    假设某部雷达系统的中频发射信号为13位巴克码和线形调频混合调制的信号，线形调频中心频率为30MHz,调频带宽为4MHz，每一位码宽为1μs，发射信号的帧周期为1ms。
    该雷达具有数字化正交解调，数字脉冲处理，固定目标对消，动目标检测（MTD）,和恒虚警（CFAR）处理等功能。
    假设在300km处有一个移动的点目标，多普勒频率为3.5KHz,在67.5处有一个固定点目标。
    对该系统发射波形，并进行目标检测的整个过程进行MATLAB仿真，仿真程序如下：


close all;clear all ; 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1μs
fc=28e6;   %调频信号起始频率
f0=30e6;   
fs=100e6;  %采样频率
ts=1/fs;   
B=4e6;     %调频信号宽度
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*fs*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('混合调频信号(13位巴克码+线形调频)');
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')；
%%%%%%%%%%%%%%%%%产生脉冲压缩系数%%%%%%%%%%%%%%%%
%----------------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);                 %这是采用50阶cheby窗的FIR低通滤波器
[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);                    %截取有效信息
fbb_q=fbb_q(26:end);                    %截取有效信息
fbb=fbb_i+j*fbb_q;

%--------------产生理想线形调频脉冲压缩匹配系数----%
N=131126;     %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);               %第一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)')；
sublot(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);
local_oscillator_q=sin(n*f0/fs*2*pi);
fbb_i=local_oscillator_i.*s;
fbb_q=local_oscillator_q.*s;
window=chebwin(51,40);
[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);                    %截取有效信息
fbb_q=fbb_q(26:end);                    %截取有效信息
signal=fbb_i+j*fbb_q;
clear fbb_i;
clesr fbb_q;

signal_fft=fft(signal1,M);
pc_result_fft=signal_fft.*match_filter_1_fft;
pc_result=ifft(pc_rsult_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_filter_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;          %动目标的多普勒频率
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_cho_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_fibj_pulse,1,N_echo_frame);

t_clutter=700e-6;      %杂波位置
t_clurrer_pulse=39e-6;
sigma=2;            %瑞利分布参数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     %产生瑞利分布信号1
s_echo_clutter_pulse=[zeros(1,t_clutter/ts),echo_clutter,zreos(1,(T_framr-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_clutter;
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*2*pi);     %I路本振信号
local_oscillator_q=sin(n*f0/fs*2*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);                    %这是采用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);                %截取有效信息
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_echo_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);
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:N_echo_frame*T_ts,real(s_pc_result_1)),
xlabel('t(单位:s)'),title('脉冲压缩处理后结果(实部)')；
subplot(2,1,2),plot(0:ts:N_echo_frame*T_ftame-ts,imag(s_pc_result_1)),
xlabel('t(单位:s)'),title('脉冲压缩处理后结果(虚部)')；

%%%%%%%%%%%%%%%%%%%固定杂波对消处理%%%%%%%%%%%%%%%%%%%
for i=1:16
   s_MIT_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:N_echo_frame*T_frame-ts,real(s_MTI_result_1));
xlabel('t(单位:s)'),title('固定杂波对消后结果(实部)')；
subplot(2,1,2),plot(0:ts:N_echo_frame*T_frame-ts,imag(s_MTI_result_1));
xlabel('t(单位:s)'),title('固定杂波对消后结果(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(max(s_MTD_result_1));
end

figure,plot(0:ts:N_echo_frame*T_frame-ts,s_MTD_result),
xlabel('t(处理：s)'),title('MTD处理后求模结果(信号最大通道)')；

%%%%%%%%%%%%%%%%%%%CFAR处理%%%%%%%%%%%%%%%%%%%%%%%%%
N=T_frame/ts;
cfar_result(1,1)=s_MTD_result(1,1)/(sqrt(2)/pi*mean(s_MTD_result1,2:17));%第1点恒虚警处理时的噪声均值由其后面的16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值由其前面和后面16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16个点的噪声中的大者决定
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
%倒数第16点到倒数第2点恒虚警处理的噪声均值由其前面16点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
%最后一点的恒虚警处理的噪声均值由其前面16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_echo_frame*T_frame-ts,cfar_result),xlable('t(单位:s)'),
title('采用恒虚警处理处理结果')；