Resolution of range and Doppler ambiguities in medium PRF radars in multiple-target environment
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Bibliographic record
Abstract
In medium pulse-repetition frequency (PRF) radars, ambiguities may arise in both range and Doppler measurements. Efficient techniques have been established [1,2] to resolve the range ambiguity of a single isolated target using multiple PRF's. In this paper, we describe a simple algorithm to resolve the Doppler ambiguity using the discrete Fourier transform (DFT) output of two PRF's. A condition on the relative values of the two PRF's is derived to account for the errors due to the finite bandwidth of DFT filters. A third PRF is used to identify the declarations of a particular target in different PRF's. Range ambiguities are then resolved in a straightforward manner. A fourth PRF is made use of to extract blind-speed targets. The proposed method is computationally efficient and can be used even when ambiguous returns from several targets are received.
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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