正弦信号频谱分析实验
实验目标
【1】设定采样率fs，生成正弦波，频率为f0，量化比特数为Q，幅度为A，采集N点正弦波，用W窗对采样帧加窗，然后进行N点的FFT分析，观察对数尺度下的幅度谱S。
参考实验：
频率f0=20.0E3，量化比特数Q=12，幅度A=10；N=512，W窗为kaiser窗
%///////////////////////////////////////////////////////////
% DFT analyse of sampled sine signal
%///////////////////////////////////////////////////////////
close all;
clear;
clc;
% generate 2 sampled sine signals with different frequency（生成2个不同频率的采样正弦信号）
freq_x1 = 20.0E3 ; % frequency of signal x1
amp_x1 = 10 ; % amptitude of signal x1
freq_x2 = 30.0E3 ; % frequency of signal x2
amp_x2 = 10 ; % amptitude of signal x2
data_len = 512 ; % signal data length
fs = 512E3 ; % sample rate（采样率）
quant_bits = 12 ; % signal quant bits（信号量化比特数）
kaiser_beta = 8 ; % beta of kaiser win
idx_n = [0:data_len-1]; % n index
idx_n = idx_n .' ; % we need column vector（列向量）
idx_t = idx_n/fs ; % time index
idx_phase_x1 = 2*pi*idx_n*freq_x1/fs; % x1 phase index（x1相位指数）
idx_phase_x2 = 2*pi*idx_n*freq_x2/fs; % x2 phase index
x1 = amp_x1*sin(idx_phase_x1);
x2 = amp_x2*sin(idx_phase_x2);
% signal x is consisted of x1 and x2;
x = x1 + x2;
max_abs_x = max(abs(x)); % abs-求数值的绝对值与复数的幅值 % normalize x to (-1,1)
x = x / max_abs_x; % quant signal, the range is (-max_q, +max_q)
max_q = 2^(quant_bits-1);
x_quant = fix(x * max_q); % plot them, use time label
figure;
set(gca,'fontsize',16); % get window function data（获取窗口函数数据）（set-设置对象属性）
win = kaiser(data_len, kaiser_beta); % windowing the data
win_x = win .* x;
win_x_quant = win .* x_quant;
h_t1 = subplot(4,1,1);plot(idx_t, x1 );grid on;
h_t2 = subplot(4,1,2);plot(idx_t, x2 );grid on;
h_t3 = subplot(4,1,3);plot(idx_t, x );grid on;
h_t4 = subplot(4,1,4);plot(idx_t, win_x);grid on;
title(h_t1, 'x1' , 'fontsize', 14);
title(h_t2, 'x2' , 'fontsize', 14);
title(h_t3, 'x=x1+x2' , 'fontsize', 14);
title(h_t4, 'windowed x', 'fontsize', 14);
% perform fft（fft变换）
x_q_fft = fft(win_x_quant) ; % get frequency index（指数）
idx_freq = -fs/2 + idx_n .* (fs / data_len);
% shift zero frequency to the data center（将0频移动到数据中心位置）
x_q_fft = fftshift(x_q_fft);
% map to amptitude dB scale
x_q_fft_abs = abs(x_q_fft);
x_q_fft_abs_dB = 20*log10(x_q_fft_abs + 1E-8);
% normalize the spectrum from 0 dB;（从0db开始归一化频谱）
max_dB = max(x_q_fft_abs_dB);
norm_spectrum = x_q_fft_abs_dB - max_dB;
figure; plot(idx_freq, norm_spectrum);grid on;
title('Normlized Spectrum ', 'fontsize', 14);实验结果如下：
频谱S
【2】对以上过程的参数， fs, f0, Q, A, N, W 进行修改，观察S的变化