[英]Length of FFT and IFFT
I have some signals which I add up to a larger signal, where each signal is located in a different frequency region. 我有一些信号,我加上一个更大的信号,每个信号位于不同的频率区域。 Now, I perform the FFT operation on the big signal with FFTW and cut the concrete FFT bins (where the signals are located) out.
现在,我使用FFTW对大信号执行FFT运算,并切断具体的FFT分档(信号所在的位置)。
For example: The big signal is FFT transformed with 1024 points, the sample rate of the signal is fs=200000
. 例如:大信号用1024点FFT变换,信号的采样率为
fs=200000
。
I calculate the concrete bin positions for given start and stop frequencies in the following way: 我通过以下方式计算给定开始和停止频率的混凝土箱位置:
tIndex.iStartPos = (int64_t) ((tFreqs.i64fstart) / (mSampleRate / uFFTLen));
and eg I get for the first signal to be cut out 16 bins. 例如,我得到第一个信号被切掉16个箱子。 Now I do the IFFT transformation again with FFTW and get the 16 complex values back (because I reserved the vector for 16 bins).
现在我再次使用FFTW进行IFFT转换并获得16个复数值(因为我保留了16个二进制数的向量)。
But when I compare the extracted signal with the original small signal in MATLAB, then I can see that the original signal (is a wav-File) has xxxxx data and my signal (which I saved as raw binary file) has only 16 complex values. 但是当我在MATLAB中将提取的信号与原始的小信号进行比较时,我可以看到原始信号(是一个wav-File)有xxxxx数据而我的信号(我保存为原始二进制文件)只有16个复数值。
So how do I obtain the length of the IFFT operation to be correctly transformed? 那么如何获得正确转换的IFFT操作的长度呢? What is wrong here?
这有什么不对?
EDIT The logic itself is split over 3 programs, each line is in a multithreaded environment. 编辑逻辑本身分为3个程序,每个行都处于多线程环境中。 For that reason I post here some pseudo-code:
出于这个原因,我在这里发布了一些伪代码:
ReadWavFile(); //returns the signal data and the RIFF/FMT header information
CalculateFFT_using_CUFFTW(); //calculates FFT with user given parameters, like FFT length, polyphase factor, and applies polyphased window to reduce leakage effect
GetFFTData(); //copy/get FFT data from CUDA device
SendDataToSignalDetector(); //detects signals and returns center frequency and bandwith for each sigal
Freq2Index(); // calculates positions with the returned data from the signal detector
CutConcreteBins(position);
AddPaddingZeroToConcreteBins(); // adds zeros till next power of 2
ApplyPolyphaseAndWindow(); //appends the signal itself polyphase-factor times and applies polyphased window
PerformIFFT_using_FFTW();
NormalizeFFTData();
Save2BinaryFile();
-->Then analyse data in MATLAB (is at the moment in work). - >然后在MATLAB中分析数据(目前在工作中)。
If you have a real signal consisting of 1024 samples, the contribution from the 16 frequency bins of interest could be obtained by multiplying the frequency spectrum by a rectangular window then taking the IFFT. 如果您有一个由1024个样本组成的实信号,则可以通过将频谱乘以矩形窗口然后采用IFFT来获得16个感兴趣频率区间的贡献。 This essentially amounts to:
这基本上相当于:
fftw_plan_dft_1d(..., FFTW_BACKWARD,...
for the inverse transform), computing the Hermitian symmetry for the upper half of the spectrum (or simply use a half-spectrum representation and perform the inverse transform through fftw_plan_dft_c2r_1d
). fftw_plan_dft_1d(..., FFTW_BACKWARD,...
用于逆变换),计算频谱上半部分的Hermitian对称性(或者简单地使用半频谱表示和通过fftw_plan_dft_c2r_1d
执行逆变换。 That said, you would get a better frequency decomposition by using specially designed filters instead of just using a rectangular window in the frequency domain. 也就是说,通过使用专门设计的滤波器而不是仅使用频域中的矩形窗口,您将获得更好的频率分解。
The output length of the FT is equal to the input length. FT的输出长度等于输入长度。 I don't know how you got to 16 bins;
我不知道你怎么到16箱; the FT of 1024 inputs is 1024 bins.
1024输入的FT是1024个箱。 Now for a real input (not complex) the 1024 bins will be mirrorwise identical around 512/513, so your FFT library may return only the lower 512 bins for a real input.
现在对于一个真正的输入(不复杂),1024个区域将在512/513左右镜像相同,因此您的FFT库可能仅返回实际输入的低512个区间。 Still, that's more than 16 bins.
不过,这还不止16个箱子。
You'll probably need to fill all 1024 bins when doing the IFFT, as it generally doesn't assume that its output will become a real signal. 在进行IFFT时,您可能需要填充所有1024个二进制位,因为它通常不会假设其输出将成为真实信号。 But that's just a matter of mirroring the lower 512 bins then.
但那只是反映了较低512个分档的问题。
声明:本站的技术帖子网页,遵循CC BY-SA 4.0协议,如果您需要转载,请注明本站网址或者原文地址。任何问题请咨询:yoyou2525@163.com.