用C Goertzel算法的实现 [英] Implementation of Goertzel algorithm in C

问题描述

我实现BFSK频率中的DSP处理器跳频通信系统。它是由一些论坛成员建议使用Goertzel算法频率的特定频率跳变解调。我曾尝试实施C.戈泽尔算法code是如下：

I am implementing BFSK frequency hopping communication system on a DSP processor. It was suggested by some of the forum members to use Goertzel algorithm for the demodulation of frequency hopping at specific frequencies. I have tried implementing the goertzel algorithm in C. the code is follows:

float goertzel(int numSamples,int TARGET_FREQUENCY,int SAMPLING_RATE, float* data)
{
    int     k,i;
    float   floatnumSamples;
    float   omega,sine,cosine,coeff,q0,q1,q2,result,real,imag;

    floatnumSamples = (float) numSamples;
    k = (int) (0.5 + ((floatnumSamples * TARGET_FREQUENCY) / SAMPLING_RATE));
    omega = (2.0 * M_PI * k) / floatnumSamples;
    sine = sin(omega);
    cosine = cos(omega);
    coeff = 2.0 * cosine;
    q0=0;
    q1=0;
    q2=0;

    for(i=0; i<numSamples; i++)
    {
        q0 = coeff * q1 - q2 + data[i];
        q2 = q1;
        q1 = q0;
    }
    real = (q1 - q2 * cosine);
    imag = (q2 * sine);
    result = sqrtf(real*real + imag*imag);
    return result;
}

当我使用的功能在特定频率来计算结果，对于一个给定的数据集，我没有得到正确的结果。但是，如果我用同样的数据集，并使用MATLAB戈泽尔（）函数计算戈泽尔结果，然后我得到的结果非常完美。我用C实现的算法，与一些在线教程，我发现在互联网上的帮助。我只是想获得你们的观点，如果函数正确执行Goertzel算法。

When I use the function to calculate the result at specific frequencies for a given dataset, I am not getting the correct results. However, if I use the same dataset and calculate the goertzel result using MATLAB goertzel() function, then I get the results perfectly. I am implemented the algorithm using C, with the help of some online tutorials that I found over the internet. I just want to get the view of you guys if the function is implementing the goertzel algorithm correctly.

推荐答案

如果你是说Matlab的实现是一件好事，因为它的结果匹配结果的DFT或数据的FFT的这个频率，那么它可能是因为作为被与FFT完成matlab实现被归由缩放因子的结果。

If you are saying that the Matlab implementation is good because its results match the result for that frequency of a DFT or FFT of your data, then it's probably because the Matlab implementation is normalizing the results by a scaling factor as is done with the FFT.

更改code，以考虑到这一点，看看它是否提高你的结果。请注意，我也改变了功能，结果名称，以反映您戈泽尔是计算的幅度，不完整的复杂结果，净度：

Change your code to take this into account and see if it improves your results. Note that I also changed the function and result names to reflect that your goertzel is calculating the magnitude, not the complete complex result, for clarity:

float goertzel_mag(int numSamples,int TARGET_FREQUENCY,int SAMPLING_RATE, float* data)
{
    int     k,i;
    float   floatnumSamples;
    float   omega,sine,cosine,coeff,q0,q1,q2,magnitude,real,imag;

    float   scalingFactor = numSamples / 2.0;

    floatnumSamples = (float) numSamples;
    k = (int) (0.5 + ((floatnumSamples * TARGET_FREQUENCY) / SAMPLING_RATE));
    omega = (2.0 * M_PI * k) / floatnumSamples;
    sine = sin(omega);
    cosine = cos(omega);
    coeff = 2.0 * cosine;
    q0=0;
    q1=0;
    q2=0;

    for(i=0; i<numSamples; i++)
    {
        q0 = coeff * q1 - q2 + data[i];
        q2 = q1;
        q1 = q0;
    }

    // calculate the real and imaginary results
    // scaling appropriately
    real = (q1 - q2 * cosine) / scalingFactor;
    imag = (q2 * sine) / scalingFactor;

    magnitude = sqrtf(real*real + imag*imag);
    return magnitude;
}

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