波达方向估计DOA
最近一直致力于语音增强方面的工作，主要是增强目标位置发出的语音信号，削弱环境噪音。这里面最有效的方法就是波达方向估计和波束增强了。本篇主要介绍波达方向估计，其包含很多种算法：capon music RSS GCC等。我这里主要是使用GCC算法，我的麦克阵列使用的是双麦克，8cm距离。以下是我写的C语言版本，由于是第一版，所以比较粗糙，不过性能还是稳定的，角度误差在20°左右，希望能帮到大家：
#include
#include
#include
#include
#include
#include
#include"tool_spline.h"
#define PI 3.1416
typedef struct PCM PCM;
typedef struct Matrix Matrix;
typedef struct X X;
typedef struct conj_X conj_X;
typedef struct max_index max_index;
typedef struct doa_res doa_res;
// 读取文件后，文件内容和文件长度
struct PCM {
int* data;
int length;
};
// 把两个麦克的数据组成矩阵
struct Matrix {
int * m[2];
int length;
};
// fft变换后，二维的频率数据
struct X {
fftw_complex* x[2];
};
// X数据的复数共轭
struct conj_X {
fftw_complex* x[2];
};
// 求取最大值和最大值的索引
struct max_index {
double data;
int index;
};
// 最终角度的数据和长度
struct doa_res {
double* data;
int n_blocks;
};
// 读取文件
PCM readPCM(char* file_path) {
FILE* file;
const int MAX_END = 2;
const int MAX_START = 0;
file = fopen(file_path, "rb");
if (file == NULL) {
printf("open file failed. file_path is :%s\n", file_path);
PCM cur_pcm = { NULL,0 };
return cur_pcm;
}
fseek(file, 0L, MAX_END);
int file_len = ftell(file);
unsigned char* origin_data = (unsigned char*)malloc(file_len + 1);
int* data = (int*)calloc(file_len / 2, sizeof(int));
fseek(file, 0L, MAX_START);
fread((char*)origin_data, 1, file_len, file);
origin_data[file_len] = '\0'; // 空字符，表示字符串的结束
int count = 0;
for (int i = 0; i < file_len - 1; i += 2) {
data[count++] = (int)((origin_data[i + 1] << 8) | origin_data[i]);
}
fclose(file);
free(origin_data);
origin_data = NULL;
struct PCM cur_pcm = { data, file_len / 2 };
return cur_pcm;
}
// 合成二维矩阵
Matrix getMatrix(char* file_path1, char* file_path2) {
PCM data1 = readPCM(file_path1);
PCM data2 = readPCM(file_path2);
// 如果两个pcm文件长度不同，我们以短的作为标准
if (data1.length > data2.length) {
data1.length = data2.length;
}
else if (data1.length < data2.length) {
data2.length = data1.length;
}
Matrix cur_m;
for (int i = 0; i < 2; i++) {
cur_m.m[i] = (int*)calloc(data1.length , sizeof(int));
}
memcpy(cur_m.m[0], data1.data, data1.length*sizeof(int));
memcpy(cur_m.m[1], data2.data, data1.length*sizeof(int));
cur_m.length = data1.length;
free(data1.data);
free(data2.data);
data1.data = NULL;
data2.data = NULL;
return cur_m;
}
// 把src中的元素拷贝到des中，同时把数据从int转化为double
void cpyInt2Double(double *des, int *src,int start,int end){
int i = 0;
int count = 0;
for (i = start; i < end; i++) {
des[count++] = (double)src[i];
}
return;
}
// 快速傅里叶变换
X fft(int start_index, int end_index, Matrix matrix,int N_L) {
fftw_plan p_left, p_right, p1_left, p1_right;
/*这里本来准备使用二维方法，不过二维方法反变换一直存在问题，所以暂且使用一维
left和right其实表示矩阵的两列，即两个麦克风接收到的数据，之所以这么表示因为
我们使用一维方式进行转换，所以需要挨个转换然后拼接，说白了就是把矩阵分开计算*/
fftw_complex *out_left;
fftw_complex *out_right;
struct X fft_X;
double *in_left;
double *in_right;
double *iout_left;
double *iout_right;
in_left = (double*)fftw_malloc(N_L * sizeof(double));
in_right = (double*)fftw_malloc(N_L * sizeof(double));
out_left = (fftw_complex*)fftw_malloc((N_L / 2 + 1) * sizeof(fftw_complex));
out_right = (fftw_complex*)fftw_malloc((N_L / 2 + 1) * sizeof(fftw_complex));
cpyInt2Double(in_left, matrix.m[0], start_index, end_index);
cpyInt2Double(in_right, matrix.m[1], start_index, end_index);
p_left = fftw_plan_dft_r2c_1d(N_L, in_left, out_left, FFTW_ESTIMATE);
p_right = fftw_plan_dft_r2c_1d(N_L, in_right, out_right, FFTW_ESTIMATE);
fftw_execute(p_left);
fftw_execute(p_right);
fft_X.x[0] = out_left[0];
fft_X.x[1] = out_right[0];
fftw_destroy_plan(p_left);
fftw_destroy_plan(p_right);
fftw_free(in_left);
fftw_free(in_right);
return fft_X;
}
// 求一个复数的共轭
void conj(fftw_complex old) {
old[1] = 0 - old[1];
}
// 获取最大值和最大值索引
max_index getMax_index(double* yy,int num) {
max_index m;
m.data = yy[0];
m.index = 0;
for (int j = 0; j < num-1; j++) {
for (int jj = j + 1; jj < num; jj++) {
if (yy[jj] >= m.data) {
m.data = yy[jj];
m.index = jj;
}
}
break;
}
return m;
}
// 波达方向估计
doa_res DOA(int fs,Matrix matrix) {
int Mic_Num = 2;
double Marray[2][2] = {0.04, 0.00, -0.04, 0.00};
int N_L = 1024;
int N = 256;
int Snap = N_L / N;
int n_blocks = floor(matrix.length / N_L);
int c = 340;
// 最终角度集合
double* angle_gcc = (double*)calloc(n_blocks, sizeof(double));
fftw_plan p;
for (int i = 0; i < n_blocks; i++) {
int start_index = i*N_L; // C语言中 索引从0开始
int end_index = (i + 1)*N_L;
X x = fft(start_index, end_index, matrix, N_L);
//TODO优化
double(*delay)[2] = (double(*)[2])calloc((Mic_Num - 1)*Mic_Num, sizeof(double));
for (int chm = 0; chm < Mic_Num - 1; chm++)
for (int chn = chm + 1; chn < Mic_Num; chn++) {
fftw_plan p;
fftw_complex* Rmn;
double* Rt;
Rmn = (fftw_complex*)fftw_malloc((N_L / 2 + 1) * sizeof(fftw_complex));
Rt = (double*)fftw_malloc(N_L * sizeof(fftw_complex));
for (int col = 0; col < (N_L / 2 + 1); col++) {
double a = (x.x[chm][col][0] * x.x[chn][col][0] + x.x[chm][col][1] * x.x[chn][col][1]);
double b = (x.x[chm][col][1] * x.x[chn][col][0] - x.x[chm][col][0] * x.x[chn][col][1]);
Rmn[col][0] = a;
Rmn[col][1] = b;
}
p = fftw_plan_dft_c2r_1d(N_L, Rmn, Rt, FFTW_ESTIMATE);
fftw_execute(p);
for (int j = 0; j < N_L; j++) {
Rt[j] /= N_L;
}
int step = 1;
double xx[1024] = { 0.0 };
double x_old[1024] = { 0.0 };
for (int j = 0; j < N_L; j += step) {
xx[j] = (double)j;
}
for (int j = 0; j < N_L; j++) {
x_old[j] = (double)j;
}
double yy[1024];
SPL(N_L, xx, Rt, N_L, x_old, yy);
max_index m = getMax_index(yy, N_L);
if (m.index < N_L / 2) {
delay[chm][chn] = (double)m.index;
}
if (m.index > N_L / 2) {
delay[chm][chn] = (double)-(N_L - m.index);
}
fftw_free(Rmn);
fftw_free(Rt);
fftw_destroy_plan(p);
}
fftw_free(x.x[0]);
fftw_free(x.x[1]);
for (int cm = 0; cm < Mic_Num - 1; cm++)
for (int cn = 0; cn < Mic_Num; cn++) {
delay[cm][cn] = delay[cm][cn] / fs*c;
}
double(*dMArray)[2] = (int(*)[2])calloc(Mic_Num*Mic_Num ,sizeof(double));
double *dDelay = (double*)calloc(Mic_Num*(Mic_Num / 2), sizeof(double));
int n = 0;
for (int chm = 0; chm < Mic_Num - 1; chm++)
for (int chn = chm + 1; chn < Mic_Num; chn++) {
for (int j = 0; j < 2; j++) {
dMArray[n][j] = Marray[chm][j] - Marray[chn][j];
dDelay[n] = -delay[chm][chn];
}
n += 1;
}
int step = 1;
double *J1 = (double*)calloc(180 / step, sizeof(double));
double Jmin = 1000.0;
int k = 0;
double phi1_f=0.0;
for (int phi = 1; phi <= 180; phi += step) {
double phi1 = phi*PI/180;
double sc[2] = { cos(phi1) ,sin(phi1) };
double new_dMArray=0;
for(int row=0;row
#include
#include
int spline(int n, int end1, int end2,
double slope1, double slope2,
double x[], double y[],
double b[], double c[], double d[],
int *iflag)
{
int nm1, ib, i, ascend;
double t;
nm1 = n - 1;
*iflag = 0;
if (n < 2)
{ /* no possible interpolation */
*iflag = 1;
goto LeaveSpline;
}
ascend = 1;
for (i = 1; i < n; ++i) if (x[i] <= x[i - 1]) ascend = 0;
if (!ascend)
{
*iflag = 2;
goto LeaveSpline;
}
if (n >= 3)
{
d[0] = x[1] - x[0];
c[1] = (y[1] - y[0]) / d[0];
for (i = 1; i < nm1; ++i)
{
d[i] = x[i + 1] - x[i];
b[i] = 2.0 * (d[i - 1] + d[i]);
c[i + 1] = (y[i + 1] - y[i]) / d[i];
c[i] = c[i + 1] - c[i];
}
/* ---- Default End conditions */
b[0] = -d[0];
b[nm1] = -d[n - 2];
c[0] = 0.0;
c[nm1] = 0.0;
if (n != 3)
{
c[0] = c[2] / (x[3] - x[1]) - c[1] / (x[2] - x[0]);
c[nm1] = c[n - 2] / (x[nm1] - x[n - 3]) - c[n - 3] / (x[n - 2] - x[n - 4]);
c[0] = c[0] * d[0] * d[0] / (x[3] - x[0]);
c[nm1] = -c[nm1] * d[n - 2] * d[n - 2] / (x[nm1] - x[n - 4]);
}
/* Alternative end conditions -- known slopes */
if (end1 == 1)
{
b[0] = 2.0 * (x[1] - x[0]);
c[0] = (y[1] - y[0]) / (x[1] - x[0]) - slope1;
}
if (end2 == 1)
{
b[nm1] = 2.0 * (x[nm1] - x[n - 2]);
c[nm1] = slope2 - (y[nm1] - y[n - 2]) / (x[nm1] - x[n - 2]);
}
/* Forward elimination */
for (i = 1; i < n; ++i)
{
t = d[i - 1] / b[i - 1];
b[i] = b[i] - t * d[i - 1];
c[i] = c[i] - t * c[i - 1];
}
/* Back substitution */
c[nm1] = c[nm1] / b[nm1];
for (ib = 0; ib < nm1; ++ib)
{
i = n - ib - 2;
c[i] = (c[i] - d[i] * c[i + 1]) / b[i];
}
b[nm1] = (y[nm1] - y[n - 2]) / d[n - 2] + d[n - 2] * (c[n - 2] + 2.0 * c[nm1]);
for (i = 0; i < nm1; ++i)
{
b[i] = (y[i + 1] - y[i]) / d[i] - d[i] * (c[i + 1] + 2.0 * c[i]);
d[i] = (c[i + 1] - c[i]) / d[i];
c[i] = 3.0 * c[i];
}
c[nm1] = 3.0 * c[nm1];
d[nm1] = d[n - 2];
}
else
{
b[0] = (y[1] - y[0]) / (x[1] - x[0]);
c[0] = 0.0;
d[0] = 0.0;
b[1] = b[0];
c[1] = 0.0;
d[1] = 0.0;
}
LeaveSpline:
return 0;
}
double seval(int n, double u,
double x[], double y[],
double b[], double c[], double d[],
int *last)
{
int i, j, k;
double w;
i = *last;
if (i >= n - 1) i = 0;
if (i < 0) i = 0;
if ((x[i] > u) || (x[i + 1] < u))
{
i = 0;
j = n;
do
{
k = (i + j) / 2;
if (u < x[k]) j = k;
if (u >= x[k]) i = k;
} while (j > i + 1);
}
*last = i;
w = u - x[i];
w = y[i] + w * (b[i] + w * (c[i] + w * d[i]));
return (w);
}
void SPL(int n, double *x, double *y, int ni, double *xi, double *yi)
{
double *b, *c, *d;
int iflag, last, i;
b = (double *)malloc(sizeof(double) * n);
c = (double *)malloc(sizeof(double) * n);
d = (double *)malloc(sizeof(double) * n);
if (!d) { printf("no enough memory for b,c,d\n"); }
else {
spline(n, 0, 0, 0, 0, x, y, b, c, d, &iflag);
// if (iflag == 0) printf("I got coef b,c,d now\n"); else printf("x not in order or other error\n");
for (i = 0; i