A novel wideband DOA estimation technique based on harmonic source model for a uniform linear array
Bibliographic record
Abstract
Wideband direction of arrival (DOA) estimation problem has attracted a lot of attention in recent years due to its practical importance in many important areas. In this paper, a wideband DOA technique is proposed. This technique is based on two main ideas: (i) the correlation between the sensor measurements of a uniform linear array (ULA) and a sine or cosine waveform with known frequency forms a sequence that may be regarded as a sinusoidal signal with multiple frequencies associated with the time delays of all the sources; (ii) the DOA estimation can then be cast into a frequency estimation problem that may be solved by utilizing the AR model of a sinusoidal signal. The DOAs are identified by a grid search based on the estimated AR model. The new technique may be applied to both incoherent as well as coherent real-valued sources of harmonic or nonharmonic nature. Furthermore, the method does not require the use of the computationally intensive singular value decomposition (SVD) operation and the a priori knowledge of the number sources. It has been demonstrated through extensive simulations that the proposed technique is advantageous compared to the other commonly used techniques, such as the incoherent wideband MUSIC (IWM) and the coherent steered covariance matrix (STCM) based methods.
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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 | 0.001 |
| 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".