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author | Matthias P. Braendli <matthias.braendli@mpb.li> | 2017-05-19 14:35:12 +0200 |
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committer | Matthias P. Braendli <matthias.braendli@mpb.li> | 2017-05-19 14:35:12 +0200 |
commit | 1133ab26f61e21e959fc73ffde576bb9bc926bf4 (patch) | |
tree | 00278c92c61a843f070d4a8f073afb94bdc9c207 | |
parent | 2f5770d4abfbc97966724a942717199047c79d10 (diff) | |
download | odr-dpd-master.tar.gz odr-dpd-master.tar.bz2 odr-dpd-master.zip |
-rw-r--r-- | AlignSample.cpp | 50 |
1 files changed, 45 insertions, 5 deletions
diff --git a/AlignSample.cpp b/AlignSample.cpp index 7de4459..0227d41 100644 --- a/AlignSample.cpp +++ b/AlignSample.cpp @@ -233,7 +233,8 @@ static std::vector<double> gen_omega(size_t length) } /* Find subsample delay in signal versus the reference signal ref and - * correct it + * correct it. This assumes that the offset between signal and ref + * is less than one sample. */ static vec_cf align_subsample(vec_cf& signal, vec_cf& ref) { @@ -246,19 +247,38 @@ static vec_cf align_subsample(vec_cf& signal, vec_cf& ref) fftw::plan plan_ifft(N, rotate_vec, corr_sig, FFTW_BACKWARD); plan.execute(); - const auto omega = gen_omega(N); + const std::vector<double> omega = gen_omega(N); + + // Calculate the correlation for a lag of tau, which + // must be between -1 and 1 samples auto correlate_point = [&](float tau) { + + // A subsample offset between two signals corresponds, in the frequency + // domain, to a linearly increasing phase shift, whose slope + // corresponds to the delay. + // + // Here, we build this phase shift in rotate_vec, and multiply it with + // our signal. for (size_t i = 0; i < N; i++) { const complexf angle(0, tau * i); - rotate_vec[i] = std::exp(angle); + rotate_vec[i] = std::exp(angle); // e^(j*tau*i) } + // zero-frequency is rotate_vec[0], so rotate_vec[N/2] is the + // bin corresponding to the [-1, 1, -1, 1, ...] time signal, which + // is both the maximum positive and negative frequency. + // I don't remember why we handle it differently. rotate_vec[N/2] = cos(M_PI * tau); for (size_t i = 0; i < N; i++) { rotate_vec[i] *= fft_sig[i]; } - plan_ifft.execute(); + plan_ifft.execute(); // corr_sig = IFFT(rotate_vec) + + // Calculate correlation only the real part of the signal: + // The following implements the elementwise vector operation + // corr_real = real(corr_sig) * real(ref) + // in an awkward way. std::vector<float> corr_real(N); std::transform(corr_sig.begin(), corr_sig.end(), corr_real.begin(), @@ -268,18 +288,38 @@ static vec_cf align_subsample(vec_cf& signal, vec_cf& ref) complexf f = corr_real[i] * ref[i]; corr_real[i] = f.real(); } + + // TODO: replace by the following and verify it's equivalent + /* + for (size_t i = 0; i < N; i++) { + corr_real[i] = corr_sig[i].real() * ref[i].real(); + } + */ + + // TODO why do we only look at the real part? Because it's faster than + // a complex cross-correlation? Clarify! + // Compare with + /* + for (size_t i = 0; i < N; i++) { + corr_real[i] = (corr_sig[i] * std::conj(ref[i])).real(); + } + */ + + // The correlation is the sum: return std::accumulate(corr_real.begin(), corr_real.end(), 0.0f); }; const float start_arg = -1; const float end_arg = 1; + // Let boost find the tau value with the minimal correlation auto tau = boost::math::tools::brent_find_minima( correlate_point, start_arg, end_arg, 1000).first; fprintf(stderr, "Fractional delay is %f\n", tau); + // Prepare rotate_vec = fft_sig with rotated phase for (size_t i = 0; i < N; i++) { const complexf angle(0, tau * i); rotate_vec[i] = std::exp(angle); @@ -289,7 +329,7 @@ static vec_cf align_subsample(vec_cf& signal, vec_cf& ref) rotate_vec[i] *= fft_sig[i]; } - plan_ifft.execute(); + plan_ifft.execute(); // corr_sig = IFFT(rotate_vec) return corr_sig; } |