Target localization for bistatic MIMO radar in unknown correlated noise
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, target localization for bistatic MIMO radar in unknown spatially correlated noise is investigated. In our model, both the transmitter and receiver arrays are divided into two subarrays. A novel target localization algorithm is proposed by jointly estimating the directions-of-departure (DODs) and directions-of-arrival (DOAs) for transmitter and receiver subarrays in unknown noise. The algorithm exploits the canonical correlation decomposition (CCD) and the joint estimation technology based on the shift-invariance properties of different subarrays obtaining the automatic pairing. In addition, the compact formulas of stochastic Cramer-Rao bounds (CRB's) for DOD and DOA estimation are derived. The simulations show that our method effectively improves the performance of estimation by eliminating the unknown correlated noise.
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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 it