Direction of Arrival Estimation of Acoustic Echoes Using Source Elimination Method
Bibliographic record
Abstract
A new method for the direction of arrival (DOA) estimation for a single narrowband acoustic source with multiple low power echoes is proposed. The mathematical relations between the signal covariance matrix, the sources steering vectors, and the power of the sources are developed in order to expose the contribution of each source. Algorithms to find each of the source's DOA and their respective power are presented. The source elimination method (SEM), based on the elimination of the contribution of each source to improve the DOA estimation, is developed. Monte Carlo simulations are presented, showing that SEM yields more accurate results than multiple signal classification (MUSIC) with forward-backward spatial smoothing (FBSS) to find the echoes' DOA with an echo-to-noise ratio between -13 and -17 dB. Experimental results show that for a small array and two sources with different power, SEM outperforms MUSIC with FBSS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".