Build notes · Goh Kun Ming
Cross-Site RF Drone Detection and Classification
Research · Public project
May 2026 – Aug 2026
Project overview
Research on cross-site radio-frequency classification, with documented evaluation limits and no deployment claim.
A research study examining whether radio-frequency drone classifiers generalise across collection sites. It compares signal representations and separates drone detection from known-identity classification. The reported evaluation did not meet every cross-site gate, so location-independent performance, publication readiness and deployment are not claimed.
Inside this build
- Audited 1,253 active captures across four sites and quarantined invalid sessions.
- Converted captures into consistent signal windows and PSD/STFT representations.
- Preregistered held-site evaluation, thresholds and acceptance criteria without tuning on the held-out site.
- Compared PSD, STFT and combined representations with clustered uncertainty estimates.
- Evaluated known-identity and unknown-identity cases separately.
- Documented failed acceptance gates and limits on deployment and generalisation.