Pre-Despreading Authenticity Verification for GPS L1 C/A Signals
Why this work is in the frame
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Bibliographic record
Abstract
The performance of GNSS receivers can be highly affected by structural interference signals such as spoofing and meaconing. The structure and power level of these signals are very similar to those of the authentic GNSS signals and as such they cannot be easily detected in the received signal set. This paper proposes a low complexity authenticity verification technique that takes advantage of the GPS signal structure in order to detect the presence of undesired structural interferences in the received signal samples. The proposed technique operates on the raw signal samples and can detect the overpowered GPS spectrum prior to signal de-spreading. This method does not need any information regarding the AGC gain and operates on digitized signal samples only. The simulation results and real data processing verify the desired performance of the proposed method even when the received signal strength (RSS) of the spoofing and authentic signals are very close to each other. Copyright © 2014 Institute of Navigation.
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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 | 0.001 | 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 it