J从PCM数据转换Android中的FFT

Question

我现在已经玩过这个了一段时间,我无法弄清楚我本来打算做什么.

我正在将PCM音频数据读入audioData数组:

 recorder.read(audioData,0,bufferSize);     //read the PCM audio data into the audioData array

我想使用Piotr Wendykier的JTransform库,以便在我的PCM数据上执行FFT以获得频率.

import edu.emory.mathcs.jtransforms.fft.DoubleFFT_1D;

目前我有这个:

       DoubleFFT_1D fft = new DoubleFFT_1D(1024); // 1024 is size of array

for (int i = 0; i < 1023; i++) {
           a[i]= audioData[i];               
           if (audioData[i] != 0)
           Log.v(TAG, "audiodata=" + audioData[i] + " fft= " + a[i]);
       }
       fft.complexForward(a);

我无法理解如何工作,有人可以给我一些指示吗？我必须在此之后进行任何计算吗？

我相信我已经离开了,任何事情都会非常感激!

本

Answer 1

如果您只是在寻找输入波形中单个正弦音的频率,那么您需要找到幅度最大的FFT峰值,其中:

Magnitude = sqrt(re*re + im*im)

i这个最大幅度峰值的指数将告诉你正弦波的大概频率:

Frequency = Fs * i / N

哪里:

Fs = sample rate (Hz)
i = index of peak
N = number of points in FFT (1024 in this case)

Answer 2

由于我花了几个小时来让它工作，这里有一个完整的 Java 实现：

import org.jtransforms.fft.DoubleFFT_1D;

public class FrequencyScanner {
    private double[] window;

    public FrequencyScanner() {
        window = null;
    }

    /** extract the dominant frequency from 16bit PCM data.
     * @param sampleData an array containing the raw 16bit PCM data.
     * @param sampleRate the sample rate (in HZ) of sampleData
     * @return an approximation of the dominant frequency in sampleData
     */
    public double extractFrequency(short[] sampleData, int sampleRate) {
        /* sampleData + zero padding */
        DoubleFFT_1D fft = new DoubleFFT_1D(sampleData.length + 24 * sampleData.length);
        double[] a = new double[(sampleData.length + 24 * sampleData.length) * 2];

        System.arraycopy(applyWindow(sampleData), 0, a, 0, sampleData.length);
        fft.realForward(a);

        /* find the peak magnitude and it's index */
        double maxMag = Double.NEGATIVE_INFINITY;
        int maxInd = -1;

        for(int i = 0; i < a.length / 2; ++i) {
            double re  = a[2*i];
            double im  = a[2*i+1];
            double mag = Math.sqrt(re * re + im * im);

            if(mag > maxMag) {
                maxMag = mag;
                maxInd = i;
            }
        }

        /* calculate the frequency */
        return (double)sampleRate * maxInd / (a.length / 2);
    }

    /** build a Hamming window filter for samples of a given size
     * See http://www.labbookpages.co.uk/audio/firWindowing.html#windows
     * @param size the sample size for which the filter will be created
     */
    private void buildHammWindow(int size) {
        if(window != null && window.length == size) {
            return;
        }
        window = new double[size];
        for(int i = 0; i < size; ++i) {
            window[i] = .54 - .46 * Math.cos(2 * Math.PI * i / (size - 1.0));
        }
    }

    /** apply a Hamming window filter to raw input data
     * @param input an array containing unfiltered input data
     * @return a double array containing the filtered data
     */
    private double[] applyWindow(short[] input) {
        double[] res = new double[input.length];

        buildHammWindow(input.length);
        for(int i = 0; i < input.length; ++i) {
            res[i] = (double)input[i] * window[i];
        }
        return res;
    }
}

FrequencyScanner将返回所呈现样本数据中主频率的近似值。它将汉明窗口应用于其输入，以允许从音频流中传入任意样本。通过在进行 FFT 变换之前对样本数据进行内部补零来实现精度。（我知道有更好的——也更复杂的——方法来做到这一点，但填充方法足以满足我的个人需求）。

我针对从 220hz 和 440hz 的参考声音创建的原始 16 位 PCM 样本进行测试，结果匹配。