Magnetic Signature Attenuation of an Unmanned Aircraft System for Aeromagnetic Survey
Why this work is in the frame
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Bibliographic record
Abstract
A novel magnetic signature attenuation technique based on reconfiguring the location and orientation of the onboard magnetic sources of an unmanned aircraft system (UAS) is presented in this paper. The UAS, GeoSurv II, is intended for high-resolution aeromagnetic survey which requires the magnetic signature of the aircraft to be very low. Genetic algorithm (GA) is used to find an optimum configuration given multiple objective functions motivated by the application. The magnetic field contribution from a single servomotor onboard GeoSurv II is modeled as a single permanent magnet dipole, which is then used to build the cost function for the GA routine. The optimization/simulation outcome suggests very little alteration in the current configuration of the GeoSurv II servomotors resulting in a substantial improvement of the overall magnetic signature of the UAS. The simulation results are validated by practical experimentation. The experimental results, in addition to the simulation results, further confirm that the GA optimized configuration substantially outperforms the current configuration in terms of magnetic signature of GeoSurv II.
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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