m基于matlab的GPS卫星信号捕获和数据解析仿真
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目录
1.算法描述
2.仿真效果预览
3.MATLAB核心程序
4.完整MATLAB
1.算法描述
GPS（全球定位系统）是一种全天时、全方位覆盖的高精度自动运行的卫星导航定位系统，在有适当接收设备的情况下向全球范围内的用户提供精确无差地测定物体运动的三维坐标和速度参数。经过长期运行已形成一个多功能综合服务系统。
卫星信号捕捉技术是现代定位接收机的关键组成环节，在实际应用中通常会结合多种处理方法以提高检测效率与精度。其中一种典型的技术方案是将传统GPS定位系统中的工作流程进行优化设计，在接收机内部引入多跳距差分相位观测器来实现高精度的位置估计功能。具体而言，在接收机内部构建了一个包含多个差分环路以及自适应滤波器组的新系统架构，在这种架构下可以通过灵活配置各跳距差分相位观测器的工作模式来实现对不同频率偏移情况的有效补偿。这种创新性设计不仅能够显著提升系统的抗干扰能力，在复杂环境下的性能表现也得到了明显改善
为了实现对GPS信号的追踪与解码,必须首先捕获该信号。接收并传输所获取的关于该GPS信号的关键参数至追踪流程后,通过追踪流程即可推导出卫星发送的数据信息。由于 GPS 卫星正处在一个高速运行的状态下,其发射出的电磁波频率会发生多普勒效应的变化。关于载波频率与 C/A 码之间的多普勒频移关系及其相关特性将在后续章节中进行详细阐述。
GPS卫星发送的信号通常主要包含三个组成部分：载波、伪码信号与导航信息。其中包含了伪码信号与导航信息的部分采用了BPSK技术进行调制处理。
为了实现目标完成对GPS信号的跟踪与解码,首要任务是捕获到相应的GPS信号.将获取的数据进行传递并利用这些数据可以顺利地完成对卫星导航信息的获取.传统的GPS捕获方式包括:串行搜索捕获,滑动相关法,循环相关法以及PMF算法等.
GPS卫星系统采用两个工作频段：f_{\text{L1}} 和 f_{\text{LO}}（注：此处可能有笔误应为f_{\text{LO}}或其他符号？根据上下文推测应为f_{\text{LO}}或其他相关符号）。这些载波信号在L频段上实现调制以减少电磁环境中的干扰问题；由于L频带的工作负荷较低且占用资源相对较少，在全球范围内提供观测服务非常高效；此外，在L频带中采用扩频技术可显著提高系统的抗干扰能力并支持宽band传输；该频带范围内的微弱大气扰动以及电离效应较小的特点使得接收设备设计更加简洁经济
2.仿真效果预览
matlab2022a仿真结果如下：
3.MATLAB核心程序
clc;
clear;
close all;
warning off;
addpath(genpath(pwd));
rng('default')
%%
%11111111111111111111111111111111111111111111111111111111111
isnoise = 0;%1:add noise;0 good signal
%nosie awgn
SNR = -19;
%Q1
satellite = [1,12,14,22];
satellitenumber = length(satellite);
fs = 16.368e6; %sampling freq
IF = 4.092e6;%centered
fIFD = IF + 5e3 - 10e3*rand(1,satellitenumber);%no more than 5 KHz in absolute value
Fai = 2*pi*rand(1,satellitenumber);%random values
Ai = 0.7+0.3*rand(1,satellitenumber);%random between 1 and 0.7 for different satellites
taoi = floor(4e5*rand(1,satellitenumber)) + 2e5; %random between 1 and
Dur = 20;%bit duration,20ms
Len = 50;%data bit length,1s
%
CHIP_TIME = 977.5e-9; % chip time in seconds
ts = 1/fs;
n = fs/1000;
nn = [0:n-1];
millisecond = 1000;
x_bound = (ts/2)/CHIP_TIME; % Maximum offset
d_samp = 6; % sample offset between correlators
d = (d_samp*ts)/CHIP_TIME;
msSamp = 16368;
for i = 1:satellitenumber
i
%C
%1ms with 16 samples
code0 = digitizg(fs/1000,fs,0,satellite(i));
%20ms
code1 = [code0,code0,code0,code0,code0,code0,code0,code0,code0,code0,code0,code0,code0,code0,code0,code0,code0,code0,code0,code0];
%len
CA = [];
for j = 1:Len
CA = [CA,code1];
end
%D
Di0 = 2*double(rand(1,Len)>=0.5)-1;
%output the data
for j = 1:Len
Dout2{i}(Dur*(j-1)+1:Dur*j) = Di0(j);
end
for j = 1:length(Dout2{i})
Di2(length(code0)*(j-1)+1:length(code0)*j) = Dout2{i}(j);
end
%S
signal0 = Ai(i).*CA.*Di2;
%16times
%delay taoi/61
delays = floor(taoi(i)/61);
signal3 = [zeros(1,delays),signal0(1:end-delays)];
%carrier
t = 0:1/fs:(length(signal3)-1)/fs;
carrier{i} = cos(2*pi*fIFD(i)*t+Fai(i));
Si0{i} = signal3.*carrier{i};
end
%noise awgn
if isnoise==0
Si_ = Si0;
else
for i = 1:satellitenumber
Si_{i} = awgn(Si0{i},SNR,'measured');
end
end
%combine
Si= Si_{1};
for i = 1:satellitenumber-1
Si = Si + Si_{i+1};
end
figure;
subplot(221);
stem(Dout2{1});
title('data bits of satelite 1');
axis([0,1000,-2,2]);
subplot(222);
stem(Dout2{2});
title('data bits of satelite 12');
axis([0,1000,-2,2]);
subplot(223);
stem(Dout2{3});
title('data bits of satelite 14');
axis([0,1000,-2,2]);
subplot(224);
stem(Dout2{4});
title('data bits of satelite 22');
axis([0,1000,-2,2]);
ttt = 0:1000/(length(Si)-1):1000;
figure;
plot(ttt,Si);
title('Combined Si');
figure;
plot(ttt(10000:10200),Si(10000:10200));
title('Combined Si local');
%%
%22222222222222222222222222222222222222222222222222
%fine frequency estimation
segment=5;
for a=1:satellitenumber
for b=1:segment
output = acquisition(Si',satellite(a),b);
correlation(:,a,b) = output{1};
correlationpeak(:,a) = output{2};
frequency(:,a,b) = output{3};
finefrequency(a,b) = output{4};
end
finefrequencyaverage(a) = mean(finefrequency(a,:));
end
finefrequencyaverage
fIFD
err = finefrequencyaverage-fIFD
X=[fIFD;finefrequencyaverage]';
figure;
bar(X);
axis([0,5,4.0e6,4.2e6]);
legend('Blue:real frequency','Red:fine frequency estimation');
xlabel('4 different satellite');
ylabel('frequency est');
%code phase
segment=5;
for a=1:satellitenumber
Data = [Si]';
for b=1:segment
output = acquisition(Data,satellite(a),b);
correlation(:,a,b) = output{1};
correlationpeak(:,a) = output{2};
frequency(:,a,b) = output{3};
finefrequency(a,b) = output{4};
end
finefrequencyaverage(a) = mean(finefrequency(a,:));
end
figure;
codephases = [];
for a=1:satellitenumber
Pdata = correlation(:,a,1);
subplot(4,1,a);
plot(Pdata);
[V,I] = max(Pdata);
hold on
plot(I,V,'r*');
xlabel('times');
ylabel('correlation');
title(['satellite',num2str(satellite(a))]);
codephases = [codephases,I];
end
%code phase of 4
codephases
taois=codephases*61
taoi
%%
%3
for a=1:satellitenumber
a
Data = [Si]';
for c=1:millisecond
%BASS method.
%use the same C/A code from BASS to correlate all 1 ms segments one at a time
cacode(:,a) = digitizg(n,fs,0,satellite(a));
%fine frequency
lc(:,a) = exp(sqrt(-1)*2*pi*finefrequencyaverage(a)*ts*nn);
lsi(:,a) = cacode(:,a).*lc(:,a);
lcf(:,a) = fft(lsi(:,a));
xf = fft(Data((c-1)*n+1:c*n));
f(:,a) = ifft(exp(-sqrt(-1)*2*pi*finefrequencyaverage(a)*ts*(c-1))*xf.* conj(lcf(:,a)));
[amp(c,a),ccn(c,a)] = max(abs(f(:,a)));
codephase(c,a) = angle((f(ccn(c,a),a)));
correlationphase(c,a) = angle((lsi(ccn(c,a),a)));
end
ccnmax(a) = max(ccn(:,a));
tmps = find(ccn(:,a)==ccnmax(a));
location(a) = tmps(1);
end
figure
for a=1:satellitenumber
subplot(4,1,a);stem(codephase(:,a));title('Correlation result');
end
figure
for a=1:satellitenumber
subplot(4,1,a);stem(correlationphase(:,a));title('Correlation Phase');
end
figure
for a=1:satellitenumber
subplot(4,1,a);stem(amp(:,a));title('Correlation Magnitude');
end
%Fine time estimate
for a=1:satellitenumber
for tt = 1:millisecond
cacode(:,a) = digitizg(n,fs,0,satellite(a));
ffreq = finefrequencyaverage(a);
code_phase = ccn(c,a);
local_carrier = exp(1i*2*pi*ffreq*ts*nn);
Data_carrier_off = [Data((tt-1)*n+1:tt*n)]'.*local_carrier;
input_ms_tt = Data_carrier_off;
corrs = ifft(fft(input_ms_tt).* [conj(fft(cacode(:,a)))]');
early = corrs(code_phase - d_samp);
late = corrs(code_phase + d_samp);
r(tt,a) = abs(late)/abs(early);
x(tt,a) = ((1-r(tt,a))*(1-d))/(1+r(tt,a));
if mod(tt,10) == 0
xx(tt/10,a) = mean(x(tt-9:tt,a)); % Average the past 10 fine time estimates
end
end
end
figure;
for i=1:satellitenumber
subplot(4,1,i);
stem(xx(:,i)*CHIP_TIME);
title('Averaged Fine Time Estimates for 10ms segments of data');
xlabel('10ms');
ylabel('Fine time Est (s)');
end
figure;
for i=1:satellitenumber
subplot(4,1,i);
stem(x(:,i)*CHIP_TIME);
title('Fine Time Estimates for 1 ms segments of data');
xlabel('1ms ');
%xlim([0,13]);
ylabel('Fine time Est (s)');
end
%%
%456together
%phase transitions
for sj=1:satellitenumber
tmps = find(amp(:,sj)>0);
start(sj) = tmps(1);
fprintf(['The initial data bits boundary from satellite ',num2str(satellite(sj)),' is : ',num2str(start(sj)),'ms\n\n']);
Recive_bits(:,sj) = Dout2{sj}(1)*ones(Len*Dur,1);
end
for sj=1:satellitenumber
%enhance the special point
corrd = [amp(:,sj)].*[amp(:,sj)].*[amp(:,sj)].*[amp(:,sj)];
corrd = corrd-min(corrd);
%find the transitions position
Count1=0;Count2=0;
for j = 3:length(corrd)-2
if corrd(j)>2*corrd(j-1) & corrd(j)>2*corrd(j+1) & corrd(j)>2*corrd(j-2) & corrd(j)>2*corrd(j+2)
Count1=Count1+1;
end
if corrd(j)<0.4*corrd(j-1) & corrd(j)<0.4*corrd(j+1) & corrd(j)<0.4*corrd(j-2) & corrd(j)<0.4*corrd(j+2)
Count2=Count2+1;
end
end
if Count1 < Count2
threshold = 0.4*mean(corrd);
Pos = find(corrd<=threshold);
else
threshold = 1.5*mean(corrd);
Pos = find(corrd>=threshold);
end
if isempty(Pos)==1
if sj == 1 ;disp('satellite 1 failed.....'); end
if sj == 12;disp('satellite 12 failed.....'); end
if sj == 14;disp('satellite 14 failed.....'); end
if sj == 22;disp('satellite 22 failed.....'); end
else
if Pos(1)==1
for j = 3:length(Pos);
Recive_bits(Pos(j-1)+1:Pos(j),sj) = -1*Recive_bits(Pos(j-1),sj);%transitions
end
else
for j = 2:length(Pos);
Recive_bits(Pos(j-1)+1:Pos(j),sj) = -1*Recive_bits(Pos(j-1),sj);%transitions
end
end
Recive_bits(Pos(end)+1:end,sj) = -1*Recive_bits(Pos(end),sj);
end
end
figure;
subplot(221);
stem(Recive_bits(:,1));title('The data bits of satellite 1');
axis([0,1000,-2,2]);
subplot(222);
stem(Recive_bits(:,2));title('The data bits of satellite 12');
axis([0,1000,-2,2]);
subplot(223);
stem(Recive_bits(:,3));title('The data bits of satellite 14');
axis([0,1000,-2,2]);
subplot(224);
stem(Recive_bits(:,4));title('The data bits of satellite 22');
axis([0,1000,-2,2]);
01-155m4.完整MATLAB
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