Question

我有一个干净的信号（曼彻斯特编码），以及包含噪声的相同信号 - 我必须用什么公式来获得信噪比？

%manchester code
T = length(bits)/bitrate; % full time of bit sequence
n = 200;
N = n*length(bits);
dt = T/N;
t = 0:dt:T;
x = zeros(1,length(t)); % output signal

for i = 0:length(bits)-1
  if bits(i+1) == 1
    x(i*n+1:(i+0.5)*n) = 1;
    x((i+0.5)*n+1:(i+1)*n) = -1;
  else
    x(i*n+1:(i+0.5)*n) = -1;
    x((i+0.5)*n+1:(i+1)*n) = 1;
  end
end

Answer 1

在Matlab中执行此操作相对容易，有几种方法。值得一提的是，信号处理工具箱中有snr - 函数。如果您没有，请使用如here所述的RMS值。

零均值信号的替代方法是使用具有标准偏差或方差的方法。 重要事项：它们仅在平均值（期望值）为零时才起作用。

这里是代码：

% random data
bits = randi(2,1,20)-1;
bitrate = 1;

% manchester code
T = length(bits)/bitrate; % full time of bit sequence
n = 200;
N = n*length(bits);
dt = T/N;
t = 0:dt:T;
x = zeros(1,length(t)); % output signal
for i = 0:length(bits)-1
  if bits(i+1) == 1
    x(i*n+1:(i+0.5)*n) = 1;
    x((i+0.5)*n+1:(i+1)*n) = -1;
  else
    x(i*n+1:(i+0.5)*n) = -1;
    x((i+0.5)*n+1:(i+1)*n) = 1;
  end
end

% add offset to test (approach with standard deviation
% and variance are NOT going to produce the correct SNR then)
%x = x + 1;

% x is the clean signal
s = x + 0.1*randn(size(x));     % noisy signal
e = s - x;                      % noise

% Matlab function in the Signal Processing Toolbox
SNR = snr(x,e)

% with RMS values
rms_x = sqrt(mean(x.^2));
rms_e = sqrt(mean(e.^2));
SNR = 10*log10((rms_x/rms_e)^2) % SNR in dB
SNR = 20*log10(rms_x/rms_e)     % SNR in dB

% with standard deviation (only for signals with zero-mean)
sigma_x = std(x);
sigma_e = std(e);
SNR = 20*log10(sigma_x/sigma_e) % SNR in dB

% with variance (only for signals with zero-mean)
var_x = var(x);
var_e = var(e);
SNR = 10*log10(var_x/var_e)     % SNR in dB

结果如下：

SNR =
   20.1780
SNR =
   20.1780
SNR =
   20.1780
SNR =
   20.1781
SNR =
   20.1781

在MATLAB中显示信噪比SNR？

1 个答案: