用matlab做adc的动态参数仿真

kongc · 发表于 2020-7-23 14:37:11

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本帖最后由 kongc 于 2020-7-23 15:02 编辑

本人最近在研究ADC，现在是用matlab做fft分析，用网上找的代码加上自己的数据，运行后频谱图结果是出来了，但是那些动态参数一个都没有计算出来，而且都提示“下标索引必须为正整数类型或逻辑类型。”，求大佬指点迷津。

kongc · 发表于 2020-7-23 15:03:34

代码如下：

%***********************************************************************%
% The following program code plots the FFT spectrum of a desired test tone.
% Test tone based on coherent sampling criteria, and computes SNR, SNDR, THD and SFDR.
% This program is believed to be accurate and reliable.
% This program may get altered without prior notification.;
% Company: xxx analog Mixed-signal Group
% Author:
% Date: 2016-01-09
%***********************************************************************%
%***********************************************************************%
% 采样时钟240MHz，输入信号频率86.25MHz，FFT点数64，ADC分辨率10bit，仿真时间400ns。
% 从cadence输出时间隔是4.16666667ns，共计97个点，从第20个点开始取64点做FFT。
% cadence输出的是归一化的结果范围是0-1.6V，需除以1.6再乘以1024，转换为数字码。
%***********************************************************************%
clear all;
clc;
datafile='ADC_result8.csv'
spectP_file='spec.csv';
%***********************************************************************%
% 输入采样时钟、样本点数、分辨率等变量
%***********************************************************************%
fs=240e6; %采样时钟
Data_Num=64; %样本点数
numbit=10; %ADC分辨率
data_start=20; %取点起始位置
fclk=fs/1e6; %x坐标轴数值显示
numpt=Data_Num;
fres=fclk/numpt; %Desired frequency resolution of FFT[MHz], fres=fclk/2^N
%***********************************************************************%
% 读取数据
%***********************************************************************%
d_in=csvread('ADC_result8.csv',1,1);
d_in=d_in/1.6*1024;
code=zeros(1,numpt);
code(1:numpt)=d_in(data_start:data_start+numpt-1);
%***********************************************************************%
% Plot output code
%***********************************************************************%
figure;
plot(code);
title(sprintf('ADC Digital Output'));
%***********************************************************************%
% Recenter the digital sine wave, for 2's complement code
%***********************************************************************%
m_ean=mean(code);
for hk=1:length(code)
code(hk)=code(hk)-m_ean;
end
%***********************************************************************%
% Display a warning, when the input generates a code greater than
% full-scale, for 2's complement code
%***********************************************************************%
max_code=max(code)
min_code=min(code)
if (max(code)>2^(numbit-1)) | (min(code)<(0-2^(numbit-1)))
%if (max(code)==2numbit -1) | (min(code)==0)
disp('Warning: ADC may be clipping!');
end
%***********************************************************************%
% Normalize input signal relative to full-scale
%***********************************************************************%
fin_dB=20*log10((max_code-min_code)/(2^numbit));
%***********************************************************************%
% 对数据样本加窗函数处理
%***********************************************************************%
% 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.
Dout=code';
Doutw=Dout;
% Doutw=Dout.*hanning(numpt);
% Doutw=Dout.*hamming(numpt);
% Doutw=Dout.*blackman(numpt);
%***********************************************************************%
% Performing the Fast Fourier Transform [FFT]
%***********************************************************************%
span=0; %Span of the input frequency on each side; span=max(round(numpt/200),5);
spanh=0; %Approximate search span for harmonics on each side
spandc=0; %Approximate search span for DC on right side
Dout_spect=fft(Doutw);
Dout_dB=20*log10(abs(Dout_spect)); %Recalculate to dB abs(Dout_spect)
spectP=(abs(Dout_spect)).*(abs(Dout_spect)); %Determine power spectrum
maxdB=max(Dout_dB(1+spandc:numpt/2));
fin=find(Dout_dB(1:numpt/2)==maxdB); %Find the signal bin number, DC=bin1
%***********************************************************************%
% Calculate SNR, SNDR, THD and SFDR values.
%***********************************************************************%
fw=fopen(spectP_file,'w'); %write the power soectrum to file
fprintf(fw,'%12.9e\n',spectP);
fclose('all');
%Find DC offset power
Pdc=sum(spectP(1:span));
%Extract overall signal power
idx1=fin-span;
idx2=fin+span;
if(idx1<=0)
idx1 = 1;
end
Ps=sum(spectP(idx1:idx2));
%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
Ph=[];
%Vector/matrix to store the sampling points responding to the harmonics
Nh=[];
%Ah represents signal and harmonic amplitude
Ah=[];
%Find harmonic frequencies and power components in the FFT spectrum
%For this procedure to work, ensure the folded back high order harmonics do not overlap
%with DC or signal or lower order harmonics , so it should be modified according to the actual condition
for har_num=1:5
tone=rem((har_num*(fin-1)+1)/numpt,1); %Input tones greater than fSAMPLE are aliased back into the spectrum
if tone>0.5
tone=1-tone; %Input tones greater than 0.5*Fsample (after aliasing) are reflected
end
Fh=[Fh tone];
%Check Nh to see the bin of the harmonics
Nh=[Nh round(tone*numpt)];
%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-spanh:har_bin+spanh))];
Ah=[Ah Dout_dB(har_bin)];
end
%Determine the total distortion power, it should be modified according to the actual condition.
Pd=sum(Ph(2:5));
%Determine the noise power
Pn=sum(spectP(1:numpt/2))-Pdc-Ps-Pd;
%Determine the next largest component
spur_max=max(max(spectP(spandc+1:fin-span-1)),max(spectP(fin+span+1:numpt/2)));
spur_bin=find(spectP(1:numpt/2)==spur_max)
%**********************计算动态特性结果**********************%
format; %设置输出格式
SFDR = 10*log10(max(spectP(1:numpt/2))/spur_max); %-fin_dB
THD = 10*log10(Pd/Ps); %+fin_dB
SNR = 10*log10(Ps/Pn); %-fin_dB
SNDR = 10*log10(Ps/(Pn+Pd)); %-fin_dB
ENOB = (SNDR-1.76)/6.02;
%disp('Note: THD is calculated from 2nd through 10th order harmonics.');
%*********************标示信号和谐波位置*********************%
%hold on;
%plot((Nh(2:10)-1).*fres,Ah(2:10)-maxdB+fin_dB,'rs');
% 标示信号
bins=(Nh(1)-1)*fres;
Ahs=Ah(1)-maxdB+fin_dB;
% 标示2次谐波
bin2=(Nh(2)-1)*fres;
Ah2=Ah(2)-maxdB+fin_dB;
% 标示3次谐波
bin3=(Nh(3)-1)*fres;
Ah3=Ah(3)-maxdB+fin_dB;
% 标示4次谐波
bin4=(Nh(4)-1)*fres;
Ah4=Ah(4)-maxdB+fin_dB;
% 标示5次谐波
bin5=(Nh(5)-1)*fres;
Ah5=Ah(5)-maxdB+fin_dB;
% 在FFT频谱图中追加标示
figure;
plot(bins,Ahs,'rs',bin2,Ah2,'rd',bin3,Ah3,'r^',bin4,Ah4,'r*',bin5,Ah5,'rx');
legend('SINGAL','HD2','HD3','HD4','HD5');
%**********************图表显示**********************%
ylabel('Full-Scale Normalized Magnitude[dB]')
xlabel('Frequency [MHz]')
title(sprintf('ADC FFT Spectrum (%g points)\nFs = %g MSps, Fin = %g MHz (%1.2gdBFS)', Data_Num,fs/1e6,(fin-1)*fres,fin_dB));
grid on;
box on;
ylim([-110 10]);
set(gca,'xgrid', 'off');
set(gca, 'GridLineStyle' ,'-');
set(gca,'yTick',[-110:10:10]);
%****************************************************%
%Display the results in the frequency domAIn with an FFT plot.
for i=0:1:numpt/2-1)
hold on;
line([i*fres,i*fres],[-110,Dout_dB(i+1)-maxdB+fin_dB],'LineWidth',2);
hold off;
end
%***********************在图中打印结果***********************%
hold on;
s1=sprintf('SFDR = %4.1fdB\n',SFDR);
s2=sprintf('THD = %4.1fdB\n',THD);
s3=sprintf('SNR = %4.1fdB\n',SNR);
s4=sprintf('SNDR = %4.1fdB\n',SNDR);
s5=sprintf('ENOB = %4.2fbit\n',ENOB);
text(25,-10,s1);
text(25,-20,s2);
text(25,-30,s3);
text(25,-40,s4);
text(25,-50,s5);
hold off;

复制代码

fightshan · 发表于 2020-7-24 14:47:47

没有必要用网上找的matlab代码，直接用波形窗口的频谱分析工具不香吗？

kongc · 发表于 2020-7-24 17:29:31

那个频谱分析工具可以算ADC的动态参数吗？我之前也研究过，但好像就是因为只有频谱图没有参数的计算才考虑代码的

kongc · 发表于 2020-7-26 15:21:44

原因找到了，下列代码中的fin值过小。fft后的dout_dB的值前两个都很大，导致fin值很小，后面的矩阵下标都是负值了，所以改了spandc的值把前两个dout_dB忽略掉就正常了。但是这样我有两个问题：一是这样忽略会不会有问题？二是为什么fft后前两个点的幅度怎么这么大，明显比后面的值大很多。