Real-Time Broadband Drone RF Signal Monitoring Using Low-Cost Multi-SDRs
Bibliographic record
Abstract
Implementing an RF scanner-type anti-drone system requires an expensive broadband receiver that collects real-time broadband drone RF signals, which change rapidly over time. In this study, we implemented a system that can monitor the spectrogram image of a wideband drone radio signal in real time using low-cost narrowband SDR equipment instead of an expensive wideband receiver. The implemented system, comprising three Adalm Pluto SDRs running in python, can monitor the spectrogram of drone RF signals in the entire 2.4 GHz ISM frequency band in real time in a typical PC environment. The performance of the implemented system was verified by measuring the RF signals generated by four types of commercial drones in an electromagnetic anechoic chamber. Combining the implemented receiver with an AI engine based on python provides the possibility of implementing a real-time anti-drone system at a low cost.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".