TinySA Ultra Drone Detection Workflow - A Visual Guide
DRONE DETECTION WORKFLOW USING THE TINYSA ULTRA
Small-Unit RF Monitoring & UAS Awareness Reference
| STEP | ACTION | PROCEDURE | OUTPUT |
|---|---|---|---|
| 1 — SETUP | Configure the TinySA Ultra | Select an antenna appropriate to the band being monitored. Use Spectrum + Waterfall display and Peak/Max Hold where useful. Establish suitable span, RBW/VBW, reference level, and gain for local conditions. | System ready for monitoring |
| 2 — SCAN | Establish the RF environment | Sweep relevant spectrum and establish a baseline of normal local activity. Watch both spectrum and waterfall displays for persistent, repeating, or newly appearing signals. Save or note signals requiring closer examination. | Spectrum baseline + active signals |
| 3 — DETECT | Find potential UAS-related emissions | Look for signal characteristics associated with digital links, telemetry, video, or other RF activity. Compare new emissions against the established baseline and observe whether signals appear, disappear, or change with suspected aircraft activity. | Potential UAS signal detected |
| 4 — IDENTIFY | Characterize the signal | Record center frequency, occupied bandwidth, relative signal strength, duration, repetition, and visible spectral characteristics. Compare observations with known/reference signatures, while avoiding identification from RF appearance alone. | Signal characterized / tentative classification |
| 5 — ASSESS | Correlate RF with other observations | Combine spectrum observations with visual, audible, thermal, or other available detection. Consider whether multiple links or aircraft may be present and whether the signal is actually unrelated Wi-Fi, telemetry, or other local RF traffic. | Higher-confidence UAS assessment |
| 6 — MONITOR | Follow changes over time | Use Max Hold and waterfall history to observe intermittent transmissions and changes in signal strength. Where lawful and appropriate, a directional receiving antenna can help determine the general direction of the strongest received signal. | Signal history + approximate direction |
| 7 — REPORT | Share observations | Record time, frequency, bandwidth, relative signal strength, suspected signal type, observations, and screenshots. Clearly distinguish confirmed observations from estimates or tentative identification. | Usable RF observation report |
QUICK MONITORING REFERENCE
| ITEM | PRACTICAL USE |
|---|---|
| Spectrum display | Shows signal energy versus frequency |
| Waterfall | Shows how RF activity changes over time |
| Max Hold | Helps reveal intermittent transmissions |
| Wideband antenna | Useful for general spectrum surveys |
| Directional antenna | Useful for comparing received signal strength by direction |
| Narrower span | Provides a closer look at a signal of interest |
| RBW/VBW | Adjust to balance sweep speed and visible signal detail |
| Screenshots/logs | Preserve observations for later comparison |
| Baseline survey | Helps distinguish routine local RF traffic from new activity |
RF AREAS WORTH MONITORING
Commercial UAS and their controllers can operate in several portions of the spectrum, with 2.4 GHz and 5 GHz ISM bands being especially common. Some systems may use other bands for control, telemetry, or video, and frequency use varies by manufacturer, model, configuration, regulatory region, and operating mode.
For that reason, do not treat a signal on a particular frequency as proof that a drone is present. Wi-Fi equipment and many other devices share these bands.
WHAT TO RECORD
A useful field log should capture:
TIME → FREQUENCY → BANDWIDTH → SIGNAL STRENGTH → DURATION/PATTERN → WATERFALL → OTHER OBSERVATIONS → ASSESSMENT
Example:
Time: 1432 local
Frequency: 5.745 GHz
Observation: New wideband emission appeared above baseline
Signal: Intermittent; relative strength increased during observation
Correlation: Unidentified quadcopter visually observed in the area
Assessment: Possible UAS-associated RF activity; identification not confirmed
Evidence: Spectrum/waterfall screenshot retained
CONTINUOUS WORKFLOW
BASELINE → SCAN → DETECT → CHARACTERIZE → CORRELATE → MONITOR → REPORT → RETURN TO SCAN
The key principle is correlation. The TinySA Ultra can show that RF energy exists and help characterize it, but the spectrum display by itself generally does not prove the transmitter is a particular drone model. Combining RF observations with visual, acoustic, thermal, Remote ID, or other authorized sensors produces a much stronger assessment.
