Inertial Measurement Aiding for an Attitude-Aided Baseline Spoofing Detection Technique
Bibliographic record
Abstract
This paper proposes a spoofing detection technique using a dual-antenna GNSS moving baseline covariance matrix with the vehicle attitude, known to some precision, to construct bounds for a spoofing detection test. When using only GNSS to construct this, the dual-antenna baseline length is compared to the known physical antenna separation. The direction cosines calculated cannot be trusted because it is not known whether a spoofing attack is influencing the solution. If an independent measurement of the attitude is introduced, a more accurate testing bound can be constructed. The proposed method is tested with real data collected on a vehicle equipped with two GNSS receivers and three different gyroscopes as it moves between being spoofed by an indoor repeater and regular GNSS operations outdoors. Results show that using a gyroscope greatly improves the test bound, and the quality of gyroscope only makes a small difference over a short time.
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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 | 0.000 | 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 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".