| """Spatial audio processing and Direction-of-Arrival (DoA) estimation.""" |
|
|
| import logging |
| import numpy as np |
|
|
| log = logging.getLogger(__name__) |
|
|
|
|
| def estimate_direction_from_mixing_matrix( |
| mixing_matrix_column: np.ndarray, |
| ) -> float: |
| """ |
| Estimate Direction of Arrival (DoA) from ICA mixing matrix column. |
| |
| Assumes 4-channel hearing aid microphone array: |
| - Channel 0: Left Front (LF) |
| - Channel 1: Left Rear (LR) |
| - Channel 2: Right Front (RF) |
| - Channel 3: Right Rear (RR) |
| |
| Args: |
| mixing_matrix_column: Single column from ICA mixing matrix (length 4) |
| |
| Returns: |
| Azimuth angle in degrees (0°=front, 90°=right, 180°=rear, 270°=left) |
| """ |
| if len(mixing_matrix_column) != 4: |
| log.warning(f"Expected 4 channel weights, got {len(mixing_matrix_column)}") |
| return 0.0 |
| |
| w = mixing_matrix_column |
| |
| |
| left_energy = (np.abs(w[0]) + np.abs(w[1])) / 2 |
| right_energy = (np.abs(w[2]) + np.abs(w[3])) / 2 |
| lr_ratio = (right_energy - left_energy) / (right_energy + left_energy + 1e-10) |
| |
| |
| front_energy = (np.abs(w[0]) + np.abs(w[2])) / 2 |
| back_energy = (np.abs(w[1]) + np.abs(w[3])) / 2 |
| fb_ratio = (front_energy - back_energy) / (front_energy + back_energy + 1e-10) |
| |
| |
| azimuth = np.degrees(np.arctan2(lr_ratio, fb_ratio)) |
| azimuth = (azimuth + 360) % 360 |
| |
| return float(azimuth) |
|
|
|
|
| def estimate_direction_from_tdoa( |
| tdoa_estimates: dict, |
| ) -> float: |
| """ |
| Estimate direction from Time Difference of Arrival (TDOA). |
| |
| Args: |
| tdoa_estimates: Dictionary with keys like 'lr_tdoa', 'fb_tdoa' |
| containing time differences in samples |
| |
| Returns: |
| Azimuth angle in degrees |
| """ |
| |
| |
| log.warning("TDOA-based DoA estimation not yet implemented") |
| return 0.0 |
|
|
