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发表于 2021-8-31 15:21:54
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matlab代码：
% x = load('C:/Users/shi_z/Desktop/x.txt');
x = (load('sar_time.mat', 'time').time)';
% y = load('C:/Users/shi_z/Desktop/y.txt');
y = (load('sar_data.mat', 'data').data)';
% length = length(y);
length = 378001;
%显示原始数据曲线图（时域）
subplot(1,1,1);
plot(x,y) ; %显示原始数据曲线图
xlabel('时间 (s)');
ylabel('被测变量y');
title('原始信号(时域)');
grid on;
format long;
%傅立叶变换
y=y-mean(y); %消去直流分量，使频谱更能体现有效信息
% fclk=(length(x)-1)/(max(x)-min(x)); %仪器的采样频率
fclk = 1e6;
numpt=length; %data.txt中的被测量个数，即采样个数
%If no window function is used, the input tone must be chosen to be unique and with
%regard to the sampling frequency. To achieve this prime numbers are introduced and the
%input tone is determined by fIN = fSAMPLE * (Prime Number / Data Record Size).
%To relax this requirement, window functions such as HANNING and HAMING (see below) can
%be introduced, however the fundamental in the resulting FFT spectrum appears 'sharper'
%without the use of window functions.
% Doutw=y;
%Doutw=y'.*hanning(numpt);
Doutw=y'.*hamming(numpt);
%Performing the Fast Fourier Transform
Dout_spect=fft(Doutw);
%Recalculate to dB
Dout_dB=20*log10(abs(Dout_spect));
%Display the results in the frequency domain with an FFT plot
figure; %建立图形
maxdB=max(Dout_dB(1:numpt/2));
%For TTIMD, use the following short routine, normalized to —6.5dB full-scale.
%plot([0:numpt/2-1].*fclk/numpt,Dout_dB(1:numpt/2)-maxdB-6.5);
%plot([0:30/2-1].*fclk/numpt,Dout_dB(1:30/2)-maxdB);
plot([0:numpt/2-1].*fclk/numpt,Dout_dB(1:numpt/2)-maxdB);
grid on;
title('FFT PLOT');
xlabel('ANALOG INPUT FREQUENCY (Hz)');
ylabel('AMPLITUDE (dB)');
a1=axis; axis([a1(1) a1(2) -120 a1(4)]);
%Calculate SNR, SINAD, THD and SFDR values
%Find the signal bin number, DC = bin 1
fin=find(Dout_dB(1:numpt/2)==maxdB);
%Span of the input frequency on each side
%span=max(round(numpt/200),5);%span=max(round(numpt/200),5);
%Approximate search span for harmonics on each side
spanh=2;%spanh=2;
%Determine power spectrum
spectP=(abs(Dout_spect)).*(abs(Dout_spect));
%Find DC offset power
%Pdc=sum(spectP(1:span));
%Extract overall signal power
Ps=sum(spectP(fin-spanh:fin+spanh));
%Vector/matrix to store both frequency and power of signal and harmonics
Fh=[];
%The 1st element in the vector/matrix represents the signal, the next element represents
%the 2nd harmonic, etc.
Ph=[];
%Find harmonic frequencies and power components in the FFT spectrum
for har_num=1:10 %har_num谐波总数
%Input tones greater than fSAMPLE are aliased back into the spectrum
tone=rem((har_num*(fin-1)+1)/numpt,1); %rem（x，y）x除以y的余数 numpt(Number of Points)
if tone>0.5
%Input tones greater than 0.5*fSAMPLE (after aliasing) are reflected
tone=1-tone;
end
Fh=[Fh tone];
%For this procedure to work, ensure the folded back high order harmonics do not overlap
%with DC or signal or lower order harmonics
%har_peak=max(spectP(round(tone*numpt)-spanh:round(tone*numpt)+spanh));
%har_bin=find(spectP(round(tone*numpt)-spanh:round(tone*numpt)+spanh)==har_peak);
%har_bin=har_bin+round(tone*numpt)-spanh-1;
%Ph=[Ph sum(spectP(har_bin-1:har_bin+1))];
Ph=[Ph sum(spectP(har_num*(fin-1):har_num*(fin-1)+2))];
end
%Determine the total distortion power
Pd=sum(Ph(2:10)); %Pd总失真功率 Ph(1) is fundamental harmonic谐波 power
%Determine the noise power
Pn=sum(spectP(1:numpt/2))-Ps-Pd; %Pn噪声功率 Ps信号功率
format;%设置输出格式
SNR = 10*log10(Ps/Pn); %信噪比
SINAD=10*log10(Ps/(Pn+Pd)); % SINAD = 10*log10(Ps/(Pn+Pd)) 信号与噪声失真比
disp('THD is calculated from 2nd through 10th order harmonics');
SFDR=10*log10(Ph(1)/max(Ph(2:10))); %SFDR无杂散动态范围
ENOB = (SINAD-1.76)/6.02;
disp('Signal & Harmonic Power Components:');
HD=10*log10(Ph(1:10)/Ph(1));
s1=sprintf(' SNR(dB)=%1.3f',SNR);
s2=sprintf(' ENOB =%1.3f',ENOB);
disp(s1)
disp(s2)
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