CRealVector CNoiseReduction::OptimalFilter(const CComplexVector& veccSigFreq,
const CRealVector& vecrSqMagSigFreq,
const CRealVector& vecrNoisePSD)
{
CRealVector vecrReturn(iBlockLenLong);
/* Calculate optimal filter coefficients in the frequency domain:
G_opt = max(1 - S_nn(n) / S_xx(n), 0) */
veccOptFilt = Max(Zeros(iFreqBlLen), Ones(iFreqBlLen) -
vecrNoisePSD / vecrSqMagSigFreq);
/* Constrain the optimal filter in time domain to avoid aliasing */
vecrOptFiltTime = rifft(veccOptFilt, FftPlan);
vecrOptFiltTime.Merge(vecrOptFiltTime(1, iBlockLen), Zeros(iBlockLen));
veccOptFilt = rfft(vecrOptFiltTime, FftPlan);
/* Actual filtering in frequency domain */
vecrReturn = rifft(veccSigFreq * veccOptFilt, FftPlan);
/* Cut out correct samples (to get from cyclic convolution to linear
convolution) */
return vecrReturn(iBlockLen + 1, iBlockLenLong);
}
CReal CTimeWiener::TimeOptimalFilter(CRealVector& vecrTaps, const int iTimeInt,
const int iDiff, const CReal rNewSNR,
const CReal rNewSigma, const CReal rTs,
const int iLength)
{
int i;
CReal rFactorArgExp;
CReal rMMSE;
int iCurPos;
CRealVector vecrReturn(iLength);
CRealVector vecrRpp(iLength);
CRealVector vecrRhp(iLength);
/* Factor for the argument of the exponetial function to generate the
correlation function */
rFactorArgExp =
(CReal) -2.0 * crPi * crPi * rTs * rTs * rNewSigma * rNewSigma;
/* Doppler-spectrum for short-wave channel is Gaussian
(Calculation of R_hp!) */
for (i = 0; i < iLength; i++)
{
iCurPos = i * iTimeInt + iDiff;
vecrRhp[i] = exp(rFactorArgExp * iCurPos * iCurPos);
}
/* Doppler-spectrum for short-wave channel is Gaussian
(Calculation of R_pp!) */
for (i = 0; i < iLength; i++)
{
iCurPos = i * iTimeInt;
vecrRpp[i] = exp(rFactorArgExp * iCurPos * iCurPos);
}
/* Add SNR at first tap */
vecrRpp[0] += (CReal) 1.0 / rNewSNR;
/* Call levinson algorithm to solve matrix system for optimal solution */
vecrTaps = Levinson(vecrRpp, vecrRhp);
/* Calculate MMSE for the current wiener filter */
rMMSE = (CReal) 1.0 - Sum(vecrRhp * vecrTaps);
return rMMSE;
}
