A list,

1 Filter Filters can be divided into low pass filter (LPF), high pass filter (HPF), band pass filter (BPF) and band stop filter (BEF) according to the frequency band. In the field of rf antenna, band pass filter (BPF) is mainly used.

2 Band pass filter (BPF)



① : RF BPF: take out the effective signal of the desired frequency band from the antenna, filter out the electromagnetic wave signal and noise that do not need the frequency band.

② : RF BPF: frequency conversion with a subordinate mixer (down mixer), to prevent the introduction of interference signals in the IF band, with BPF will not expect frequency components filter out.

③ : IF BPF: Among many frequency components produced by frequency conversion from mixers, BPF only takes out the desired IF signal, which also has the effect of limiting the frequency band of the received signal.

(4) : IF BPF: frequency conversion with mixer (frequency rise converter), with BPF to prevent the introduction of interference signals in the RF band, also has the role of limiting the transmission signal band.

⑤ : RF BPF: Out of many frequency components produced by frequency conversion from mixers, only the desired RF signal is taken out with BPF.

⑥ : RF BPF: with BPF to remove the power amplifier distortion caused by the parasitic part, and the input of high power signal in the antenna switch produced by the parasitic part, so as not to transmit the parasitic components through the antenna.

3 selection of band pass filter (BPF) : (1) For low frequency circuit, select LC filter. LC filters are usually used in the fundamental frequency domain. (2) For the frequency range of 100MHz~1000MH, SAW filter was selected. SAW filters are commonly used in the IF BPF domain. (3) For 2GHz frequency circuit, select medium filter. Dielectric filters are commonly used in the RF BPF field.

4. Bandpass filter (BPF)

Core idea: BPF is basically a resonant circuit. The resonant circuit is divided into series resonant circuit and parallel resonant circuit. For the series resonant circuit, if L and C have no loss, the impedance becomes zero at the resonant frequency. For parallel resonant circuits, the impedance becomes infinite at the resonant frequency. For the series resonant circuit, the larger L is, the steeper the attenuation characteristic is; For parallel resonant circuit, the smaller L, the larger C, the steeper the attenuation characteristic.

Resonant frequency of resonant circuit:





Combined circuit of series resonance and parallel resonance:



5 Medium filter



Six microstrip lines make filter

Ii. Source code

clear all;
file_name = 'Data1.txt'; % file_name fid =fopen(file_name,'r'); % open file h=fgets(fid); % drop the first line; C=textscan(fid,'%*f%f%f%f%f'); % drop the first column; And write the other rows and columnsC
fclose(fid); % close file Data=[C{1}'; C{2}'; C{3}'; C{4}']; Data1 fid =fopen(['new_' file_name],'w'); % Open a new folderfprintf(fid,'%-.10e %-.10e %-.10e %-.10e\r\n ',Data); % Put the removed data into a new folder, pure data FCLOSE (FID); % Closes the new folder %load'new_Data1.txt';
t=['new_' file_name];
[newData]=textread(t,'a', 'delimiter'.' ');

x1=newData(:,1);
x2=newData(:,2);
x3=newData(:,3);
x4=newData(:,4);

figure(1);
subplot(4.1.1)
plot(x1);
axis([0 512 0.5 1.7]); grid on; % figure; subplot(4.1.2)
plot(x2);
axis([0 512 0.5 1.7]); grid on; % figure; subplot(4.1.3)
plot(x3);
axis([0 512 0.5 1.7]); grid on; % figure; subplot(4.1.4)
plot(x4);
axis([0 512 0.5 1.7]); grid on; N=512;
M=1; % regulator fs=1000; % data points % time series n=0:N- 1; f=n*fs/N; Frequency sequence % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % signal figure (2); y1=fft(x1,N); % Perform the fast Fourier transform mag1=abs(y1); % Obtain the amplitude subplot of Fourier transform (4.1.1) ,plot(f(1:N/2),mag1(1:N/2));
axis([0 500 0 20]); grid on; y2=fft(x2,N); % Perform the fast Fourier transform mag2=abs(y2); % Obtain the amplitude subplot of Fourier transform (4.1.2), plot(f(1:N/2),mag2(1:N/2));
axis([0 500 0 20]); grid on; y3=fft(x3,N); % Perform the fast Fourier transform mag3=abs(y3); % Obtain the amplitude subplot of Fourier transform (4.1.3) ,plot(f(1:N/2),mag3(1:N/2));
axis([0 500 0 20]); grid on; y4=fft(x4,N); % Perform the fast Fourier transform mag4=abs(y4); % Obtain the amplitude subplot of Fourier transform (4.1.4), plot(f(1:N/2),mag4(1:N/2));
axis([0 500 0 20]); grid on; %=====%part3%===========% bandpass filter %========% Wp = [50 150] /1000; Ws = [10 500] /1000;
Rp = 1; Rs =50;
[n,Wn] = buttord(Wp,Ws,Rp,Rs)
[b1,a1] = butter(n,Wn);
figure(3)
freqz(b1,a1)
title('n=4 Butterworth Bandpass Filter'); Part3% = = = = = % % = = = = = = = = = = = % bandpass filter % = = = = = = = = = = = = = % % % part4% = = = = = = = = = = = %50Hz trap %=======% Wp = [10 500] /1000; Ws = [49 51] /1000;
Rp = 1; Rs = 50;
[n,Wn] = buttord(Wp,Ws,Rp,Rs)
[b2,a2] = butter(n,Wn,'stop');
figure(4)
freqz(b2,a2)
title('n=2 Butterworth Bandstop Filter');
%=====%part4%===========%50Hz trap % = = = = = = = = = = = = % % % part5% = = = = = = = = = = = = = % digital filtering % = = = = = = = = % x1 = filter (b1 and a1, x1); x1=filter(b2,a2,x1); x2=filter(b1,a1,x2); x2=filter(b2,a2,x2); x3=filter(b1,a1,x3); x3=filter(b2,a2,x3); x4=filter(b1,a1,x4); x4=filter(b2,a2,x4); figure(5);
subplot(4.1.1) plot(x1); grid on; axis([0 512 0.5 0.5])
subplot(4.1.2) plot(x2); grid on; axis([0 512 0.5 0.5])
subplot(4.1.3) plot(x3); grid on; axis([0 512 0.5 0.5])
subplot(4.1.4) plot(x4); grid on; axis([0 512 0.5 0.5]) % = = = = = % part5% = = = = = = = = = = = = = % digital filtering % = = = = = = = = % figure (6); y1=fft(x1,N); % Perform the fast Fourier transform mag1=abs(y1); % Obtain the amplitude subplot of Fourier transform (4.1.1) ,plot(f(1:N/2),mag1(1:N/2));
axis([0 500 0 11]); grid on; y2=fft(x2,N); % Perform the fast Fourier transform mag2=abs(y2); % Obtain the amplitude subplot of Fourier transform (4.1.2), plot(f(1:N/2),mag2(1:N/2));
axis([0 500 0 10]); grid on; y3=fft(x3,N); % Perform the fast Fourier transform mag3=abs(y3); % Obtain the amplitude subplot of Fourier transform (4.1.3) ,plot(f(1:N/2),mag3(1:N/2));
axis([0 500 0 10]); grid on; y4=fft(x4,N); % Perform the fast Fourier transform mag4=abs(y4); % Obtain the amplitude subplot of Fourier transform (4.1.4), plot(f(1:N/2),mag4(1:N/2));
axis([0 500 0 10]); grid on; Part6% = = = = = % % = = = = = = = = = = = = = % validation effect % = = = = = = = = % iemg1 = sum (abs(x1))/length(x1);
iemg2=sum(abs(x2))/length(x2);
iemg3=sum(abs(x3))/length(x3);
iemg4=sum(abs(x4))/length(x4);
Copy the code

3. Operation results













Fourth, note

Version: 2014 a