FAA Unmanned Aircraft Systems Sighting Reports: A Preliminary Survey
Ralph O. Howard Jr.
AIAA Aviation 2023 · 2023
A statistical baseline survey of 1,317 FAA UAS sighting reports (July 2020–March 2021) characterizes geographic distribution, altitude profiles, and detection-method breakdowns to establish a discrimination threshold for anomalous aerial events within routine drone-traffic data.
Brief
Howard (2023) analyzed 1,317 reports filed with the FAA between July 2020 and March 2021, mapping where UAS sightings cluster spatially, at what altitudes they occur, and how they were detected. The study's stated purpose is to build a quantitative baseline against which candidate-anomalous reports can be compared, flagging encounters that fall outside the established behavioral envelope of known drone operations. Altitude profiles and sensor-type breakdowns form the primary analytic axes. Presented at AIAA Aviation 2023, the work is among the first systematic treatments of the FAA UAS sighting corpus as a UAP-adjacent research dataset.
Metadata
- Category
- Search
- Venue
- AIAA Aviation 2023
- Type
- Conference proceedings
- Year
- 2023
- Authors
- Ralph O. Howard Jr.
- Access
- Paywalled
- Instruments
- FAA UAS sighting database, radar, FLIR, ADS-B
- Data sources
- FAA UAS Sighting Reports
- Tags
- UAP-data, UAS, airspace-safety, anomaly-detection, drone-surveillance, baseline-analysis
Key points
- Sample of 1,317 FAA UAS sighting reports spans July 2020 through March 2021, roughly nine months of national-airspace data, averaging approximately 146 formal reports per month.
- Geographic distribution analysis maps sighting density across U.S. airspace, with expected clustering near airports, terminal control areas, and high-population corridors.
- Altitude profiles characterize the vertical distribution of reports relative to the FAA's 400-foot AGL recreational ceiling, providing a reference threshold for anomaly flagging.
- Sensor-type breakdown distinguishes detection modalities, visual, radar, FLIR, ADS-B correlation, allowing assessment of report reliability by evidence class.
- The baseline is framed explicitly as a discrimination tool: reports falling outside established geographic, altitude, and sensor-type norms become candidates for further anomaly investigation.
- The dataset predates widespread FAA Remote ID compliance, meaning many reported UAS lacked trackable electronic identification, leaving prosaic origin unconfirmable in a significant fraction of cases.
Most interesting
- The FAA UAS sighting database captures reports from pilots and air traffic controllers, meaning some entries may inadvertently document anomalous aerial phenomena that resisted classification as conventional drones at the time of filing.
- The survey window (July 2020–March 2021) falls during a period of significantly reduced commercial aviation traffic post-COVID, which may have elevated detection sensitivity by clearing airspace of routine background traffic.
- Formal FAA sighting filings almost certainly represent only a small fraction of actual visual encounters, pilots who dismiss a sighting as an ordinary drone rarely file a report, creating systematic undercounting bias in the baseline.
- The AIAA venue signals a disciplinary shift: aerospace engineers, not astronomers or defense analysts, are now formally treating anomalous airspace events as an engineering-class research problem requiring rigorous data infrastructure.
- Radar-confirmed UAS reports and single-witness naked-eye accounts carry fundamentally different evidentiary weight, yet that distinction is rarely parsed in public UAP discourse; Howard's sensor-type breakdown is a methodological corrective.