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:
pyroomacoustics.doa.doa.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