matlab的滤波器仿真——低通滤波器与插值滤波器

项目里面有用到插值滤波器的场合，用matlab做了前期的滤波器性能仿真，产生的滤波器系数保存下来输入到FPGA IP中使用即可。

下面是仿真的代码

 % clear all
 close all

 Nx = ;
 Tx = ;
 nx = :Nx-;
 x = sin(*pi**nx/Tx);
 L = ;
 % Ny = L * Nx;
 % ny = :Ny-;
 % yi = zeros(,Ny);
 % yi(:L:Ny) = x;
 % figure;
 % stem(yi);

 Fst1 = 0.05;
 Fp1 = 0.09;
 Fp2 = 0.11;
 Fst2 = 0.15;
 Ast1 = ;
 Ap = 0.01;
 Ast2 = ;
 % bandpass filter works well, try lowpass to check whether DC signal affects pm
 % hband = fdesign.bandpass('Fst1,Fp1,Fp2,Fst2,Ast1,Ap,Ast2',Fst1,Fp1,Fp2,Fst2,Ast1,Ap,Ast2);
 hband = fdesign.lowpass('Fp,Fst,Ap,Ast',Fp2,Fst2,Ap,Ast2);
 Hband = design(hband);
 info(Hband);     %show filter info

 Fp   = 0.08   %pass band corner freq
 Fst  = 0.24   %stop band corner freq
 Ap   = 0.01;         %pass band attenuation(dB)
 Ast  = 80.0;       %stop band attenuation(dB)
 h1 = fdesign.interpolator(L,'lowpass',Fp,Fst,Ap,Ast);
 Href = design(h1);
 info(Href);     %show filter info
 fvtool(Hband,,Href,);  %show freq response
 title('lowpass filter & interpolator filter');
 legend('lowpass filter','interpolator filter');

 % import sample_dara
 a=dlmread('1.prn');%以字符形式打开文件
 v1=a(:,); %16进制转化为10进制数，存储进v1矩阵
 figure;
 subplot(,,);
 plot(v1);
 v2 = filter(Hband,v1);
 subplot(,,);
 plot(v2);
 y = filter(Href,v2);
 subplot(,,);
 plot(y);
 % b=dlmread('2.prn');%以字符形式打开文件
 % y=b(:,); %16进制转化为10进制数，存储进v1矩阵

 fft_analysis_func(v2,//, );
 legend('lowpass filter');
 fft_analysis_func(y,*L//, );
 legend('interpolator filter');

 %axis([  - ])   %zoom-in  to 25MHz
 %generating the coe file
 ref_filter = Hband.Numerator;
 gen_coe_rad10(Hband.Numerator,'lowpass_filter_rad10.coe');
 ref_filter = Href.Numerator;
 gen_coe_rad10(Href.Numerator,'inter_filter_rad10.coe');

代码中用到了两个函数

function fft_analysis_func(x, fs, adc_width)

%The following program code plots the FFT spectrum of a desired test tone. Test tone based on coherent sampling criteria, and
%computes SNR, SINAD, THD and SFDR.
%This program is believed to be accurate and reliable. This program may get altered without prior notification.;

%fid=fopen('F:\pelican_ADC_test\vjtag_prj\data_analysis\single_tone.txt','r');
%numpt=input('Number of  Points in FFT? ');
%fclk=input('Sampling Frequency (MHz)? ');
%numbit=input('ADC Resolution (bits)? ');

% numpt=length(x);
numpt = ;
fclk=fs;
numbit=adc_width;

v1 = x(:numpt);

code=v1';

%Warning: ADC output may be clipping - reduce input amplitude
if (max(code)==2^numbit-1) | (min(code)==0)
  disp('WARNING: ADC OUTPUT MAYBE CLIPPING - CHECK INPUT AMPLITUDE!');
end

Dout=code;
Voltage=Dout./((2^numbit-1)/2)*(0.5);

Doutw=(Dout').*blackmanharris(numpt);               %add Minimum -term Blackman-Harris window
Dout_spect=fft(Doutw);
Dout_dB=*log10(abs(Dout_spect));

figure;
maxdB=max(Dout_dB(:numpt/));     %numpt points FFT result in numpt/ points spectrum

%计算距离满量程的幅度差
max_voltage=max(Voltage);
delta_amplitude=*log10(max_voltage/0.5);      %full scale voltage amplitude is .5v

plot([:numpt/-].*fclk/numpt,Dout_dB(:numpt/)-maxdB+delta_amplitude);
% plot([:numpt-].*fclk/numpt,Dout_dB(:numpt)-maxdB+delta_amplitude);
grid on;
title('SINGLE TONE FFT PLOT');
xlabel('ANALOG INPUT FREQUENCY (MHz)');
ylabel('AMPLITUDE (dBfs)');

hold off;

function gen_coe_rad10(filt_num, fileName)
%max number of coefficients
num_coeffs = numel(filt_num)
fileId = fopen(fileName,'w');
%header if COE file
fprintf(fileId,'radix = 10;\n');
% first coefficient
fprintf(fileId,'coefdata = \n');
for i =  : num_coeffs-
    fprintf(fileId,'%8.9f,\n',filt_num(i));
end
% last coefficient
fprintf(fileId,'%8.9f;',filt_num(num_coeffs));
fclose(fileId);
end

仿真出的结果如下：

产生了用于滤波器的系数：

 radix = ;
 coefdata =
 -0.001219138,
 -0.002838337,
 -0.005111633,
 -0.007197151,
 -0.007796326,
 -0.005351278,
 0.001364815,
 0.012476464,
 0.026308774,
 0.039101106,
 0.045443072,
 0.039549550,
 0.017241585,
 -0.021849408,
 -0.072532419,
 -0.123501332,
 -0.158497326,
 -0.159275461,
 -0.109905781,
 -0.001430991,
 0.164384860,
 0.373413481,
 0.600371089,
 0.812911647,
 0.977825248,
 1.067924092,
 1.067924092,
 0.977825248,
 0.812911647,
 0.600371089,
 0.373413481,
 0.164384860,
 -0.001430991,
 -0.109905781,
 -0.159275461,
 -0.158497326,
 -0.123501332,
 -0.072532419,
 -0.021849408,
 0.017241585,
 0.039549550,
 0.045443072,
 0.039101106,
 0.026308774,
 0.012476464,
 0.001364815,
 -0.005351278,
 -0.007796326,
 -0.007197151,
 -0.005111633,
 -0.002838337,
 -0.001219138;