aspcol.soundfieldestimation.inf_dimensional_shd_dynamic

aspcol.soundfieldestimation.inf_dimensional_shd_dynamic(p, pos, pos_eval, sequence, samplerate, c, reg_param, dir_coeffs=None, verbose=False)

Estimates the RIR at evaluation positions using data from a moving microphone using Bayesian inference of an infinite sequence of spherical harmonics

Implements the method in J. Brunnström, M.B. Moeller, M. Moonen, “Bayesian sound field estimation using moving microphones”

Assumptions: The noise covariance is a scaled identity matrix The data is measured over an integer number of periods of the sequence N = seq_len * M, where M is the number of periods that was measured The length of sequence is the length of the estimated RIR

Parameters:

  • p (ndarray of shape (N)) – sound pressure for each sample of the moving microphone

  • pos (ndarray of shape (N, 3)) – position of the trajectory for each sample

  • pos_eval (ndarray of shape (num_eval, 3)) – positions of the evaluation points

  • sequence (ndarray of shape (seq_len) or (1, seq_len)) – the training signal used for the measurements

  • samplerate (int)

  • c (float) – speed of sound

  • reg_param (float) – regularization parameter

  • dir_coeffs (ndarray of shape (N, num_coeffs), optional) – harmonic coefficients of microphone directivity, if not supplied, the directivity is assumed to be omnidirectional. Note that a higher number of coefficients will drastically increase the computational cost

  • verbose (bool, optional) – if True, returns diagnostics, by default False

Returns:

shd_coeffs – time-domain harmonic coefficients of the estimated sound field

Return type:

ndarray of shape (num_real_freqs, num_eval)