DOA estimation from temporally and spatially correlated narrowband signals with noncircular sources
Bibliographic record
Abstract
In this paper, we develop for the first time a method of estimating the DOA parameters assuming noncircular and spatially and temporally correlated signals. The new approach is based on the two-sided IV-SSF method (instrumental variable signal with subspace fitting). It will be shown that our newly developed method outperforms the classical two-sided IV-SSF in terms of lower bias and error variance. Its performance improvement increases as the noncircularity rate increases. Moreover, this improvement is more prominent at low SNR values. We also derive for the first time an analytical expression for the stochastic Cramér-Rao bound (CRB) of the DOA estimates from spatially and temporally correlated signals generated from noncircular sources. The new CRB is compared to that of circular and temporally correlated signals. It will be shown that the CRB obtained assuming both noncircular sources and temporally correlated signals is lower than the CRB derived considering only the temporal correlation. This illustrates the potential gain that both the noncircularity and the temporal correlation provide when considered together.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".