Broadband beamforming of multiplet line arrays using subband optimal beamformers eliminating port/starboard ambiguity
Bibliographic record
Abstract
Abstract Development of beamforming methods for towed sonar multiplet line arrays is stimulated by their increased use in undersea surveillance. Such methods employ various forms of narrowband optimal beamforming to resolve port/starboard ambiguity present when the array is conventionally beamformed. In this paper, we depart from the purely narrowband approach and discuss methods for port/starboard ambiguity rejection (PSAR) using a broadband formulation. The proposed methodology relies on subband beamforming for which we use non-adaptive variants of beamspace Minimum Variance Distortionless Response (MVDR) and the Linear Constraint Minimum Variance (LCMV) beamformers. We provide detailed description and comparison of both subband methods and establish a connection between them. The paper provides assessment of PSAR properties of the developed broadband beamformers using outputs of signal processing of both simulated and experimental sonar data. Experimental data for this work were obtained through the participation in the Littoral Continuous Active Sonar (LCAS) trials.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".