FRIDA

class pyroomacoustics.doa.frida.FRIDA(L, fs, nfft, max_four=None, c=343.0, num_src=1, G_iter=None, max_ini=5, n_rot=1, max_iter=50, noise_level=1e-10, low_rank_cleaning=False, stopping='max_iter', stft_noise_floor=0.0, stft_noise_margin=1.5, signal_type='visibility', use_lu=True, verbose=False, symb=True, use_cache=False, **kwargs)

Bases: DOA

Implements the FRI-based direction of arrival finding algorithm [FRIDA].

Note

Run locate_sources() to apply the CSSM algorithm.

Parameters

  • L (ndarray) – Contains the locations of the microphones in the columns

  • fs (int or float) – Sampling frequency

  • nfft (int) – FFT size

  • max_four (int) – Maximum order of the Fourier or spherical harmonics expansion

  • c (float, optional) – Speed of sound

  • num_src (int, optional) – The number of sources to recover (default 1)

  • G_iter (int) – Number of mapping matrix refinement iterations in recovery algorithm (default 1)

  • max_ini (int, optional) – Number of random initializations to use in recovery algorithm (default 5)

  • n_rot (int, optional) – Number of random rotations to apply before recovery algorithm (default 10)

  • noise_level (float, optional) – Noise level in the visibility measurements, if available (default 1e-10)

  • stopping (str, optional) – Stopping criteria for the recovery algorithm. Can be max iterations or noise level (default max_iter)

  • stft_noise_floor (float) – The noise floor in the STFT measurements, if available (default 0)

  • stft_noise_margin (float) – When this, along with stft_noise_floor is set, we only pick frames with at least stft_noise_floor * stft_noise_margin power

  • signal_type (str) –

    Which type of measurements to use:

    • ’visibility’: Cross correlation measurements

    • ’raw’: Microphone signals

  • use_lu (bool, optional) – Whether to use LU decomposition for efficiency

  • verbose (bool, optional) – Whether to output intermediate result for debugging purposes

  • symb (bool, optional) – Whether enforce the symmetry on the reconstructed uniform samples of sinusoids b

References

FRIDA

H. Pan, R. Scheibler, E. Bezzam, I. Dokmanic, and M. Vetterli, FRIDA: FRI-based DOA estimation for arbitrary array layouts, Proc. ICASSP, pp 3186-3190, 2017