Illegal and unlicensed broadcast transmitter detection
Spaceborne wideband receivers can detect and geolocate HF, VHF, and FM broadcast transmitters operating outside licensed frequency, power, or geographic limits. This page explains the physics, the sensors, and the hard limits regulators need to understand before commissioning a campaign.
Sensors
- HawkEye 360 RF constellation: Cluster-flight architecture with three or more satellites flying in formation enables time-difference-of-arrival and frequency-difference-of-arrival (TDOA/FDOA) geolocation. Published geolocation accuracy is typically 1–5 km CEP depending on signal duration and geometry. Coverage of any given point on Earth occurs multiple times per day across the full HF–VHF–UHF spectrum.
- Spire Global SDR payload: Software-defined radio payloads hosted on Spire's LEMUR-2 cubesat constellation. Configurable frequency coverage allows tasking across HF and VHF broadcast bands. Revisit is frequent given the constellation size (100+ satellites), though geolocation precision from a single satellite is lower than cluster-flight systems; TDOA requires coordinated passes.
- TechDemoSat-1 SDR (historical): UK Space Agency technology demonstrator operated 2014–2019. Carried a wideband SDR that demonstrated detection of FM broadcast carriers and HF signals from LEO, establishing proof-of-concept for spaceborne broadcast monitoring. No longer operational but its published results underpin current system design.
- NOAA/NESDIS GOES and polar sounders (context only): Not RF-monitoring sensors, but the ITU Radio Regulations framework against which illegal transmitters are judged relies on coordination with NOAA and ITU databases. Understanding the licensed landscape is a prerequisite for declaring a signal illegal.
Why a carrier wave is hard to disguise
Every broadcast transmitter produces a continuous or near-continuous carrier at a defined frequency. That carrier radiates in all directions, including upward. A satellite passing overhead with a sufficiently sensitive wideband receiver will see the signal, provided the transmitter's effective radiated power clears the noise floor at orbital altitude. For FM broadcast (87.5–108 MHz) and international HF shortwave (3–30 MHz), transmitters routinely operate at kilowatts of ERP. That is not subtle.
The physics that makes detection possible also creates the first honest complication. A spaceborne receiver integrating over a 5–10 minute pass collects a snapshot, not a continuous watch. A pirate station that transmits for two hours at dawn and then goes silent may be missed on any given orbit. Detection confidence is a function of revisit rate multiplied by transmission duty cycle. A station on air for less than 20% of the day requires either a dense constellation or a targeted campaign with coordinated passes.
Separating one loud illegal transmitter from many quiet legal ones
The hardest problem in this use case is not detection. It is attribution. A metropolitan area may contain dozens of licensed low-power FM translators, community broadcasters, and campus stations, all occupying adjacent channels. From orbit, their aggregate spectral power can resemble a single over-powered transmitter on the same frequency. Distinguishing them requires geolocation, not just detection.
TDOA/FDOA geolocation, as demonstrated by HawkEye 360's cluster architecture, compares the time and frequency at which the same signal arrives at spatially separated satellites. The technique works well when the signal is coherent and sufficiently long-duration. For FM broadcast, where the carrier is continuous and the modulation is wideband audio, coherence is good. Geolocation accuracy of 1–5 km CEP is achievable under favourable geometry. That is precise enough to distinguish a transmitter on one side of a city from one on the other, but not to identify a specific rooftop in a dense urban block without follow-up ground investigation.
A second tool is spectral occupancy comparison against the ITU Master International Frequency Register (MIFR) and national licensing databases. If a signal appears at a frequency, power level, or geographic location inconsistent with any registered assignment, the presumption of illegality is strong. This database-matching step is analytic work, not sensor work, and it is where most of the interpretive value is added.
HF clandestine and propaganda transmitters: a different problem
Shortwave propaganda and clandestine political broadcasting present a different geometry. HF signals propagate via ionospheric skywave, meaning the transmitter may be thousands of kilometres from the intended audience. The ITU has documented cases of unregistered HF stations causing interference across multiple continents. Spaceborne detection of HF is complicated by the fact that the signal arriving at a LEO satellite (roughly 500–600 km altitude) may be a ground wave or a low-angle sky wave, not the main lobe of the antenna. Received power is therefore lower and more variable than for VHF/FM.
HF geolocation from orbit is correspondingly less precise. Published results from TechDemoSat-1 and analogous systems suggest position errors of tens of kilometres for HF, compared with the 1–5 km achievable in VHF. That is often sufficient to identify the country of origin, which is the primary regulatory question for clandestine HF, but not to locate a specific transmitter site. Ground-based direction-finding networks remain the higher-precision complement for HF attribution.
What a monitoring campaign actually looks like
A practical spaceborne illegal-transmitter campaign has three phases. The first is baseline spectral mapping: scheduled passes over the region of interest collect wideband power spectral density (PSD) data across the target bands, typically FM (87.5–108 MHz) and one or more HF sub-bands. This produces a frequency-versus-time-versus-location occupancy map.
The second phase is anomaly detection: signals that appear at frequencies, power levels, or geolocations inconsistent with the licensed database are flagged. Power estimation from orbit carries significant uncertainty because antenna gain, terrain shielding, and ionospheric conditions all affect received power. Treating the orbital power estimate as a precise ERP figure is a mistake. It is better used as a relative indicator: is this signal consistently stronger than its neighbours in ways that suggest unlicensed power?
The third phase is evidence packaging for regulators. Satellite data alone is rarely sufficient for enforcement action. What it provides is a credible, independent, time-stamped record of a signal's presence, frequency, and approximate location, which directs ground inspection teams efficiently. Satellize structures analytics outputs with this regulatory handoff in mind, drawing on the same workflow used in its Tonga crop-estimation programme: the satellite product is an input to a decision, not the decision itself.
Latency from pass to delivered report is typically 12–48 hours for non-real-time tasking. Near-real-time alerting is possible for constellations with direct-to-ground downlinks and automated processing pipelines, but adds cost and requires pre-agreed thresholds.
Honest limits: what orbit cannot do
A spaceborne receiver cannot reliably detect very low-power unlicensed transmitters. A 10-watt pirate FM station in a basement is almost certainly below the noise floor at 500 km altitude, particularly if surrounded by higher-power licensed signals on adjacent channels. The detection floor for FM from LEO is roughly in the range of several hundred watts ERP under good conditions, though this depends heavily on receiver sensitivity, integration time, and the local RF environment. Published HawkEye 360 materials do not specify a minimum detectable power for broadcast bands, and any vendor claiming sub-100-watt FM detection from LEO should be asked for the signal-to-noise analysis.
Cloud cover is irrelevant to RF monitoring, which is one genuine advantage over optical or SAR sensors for this use case. Ionospheric absorption affects HF but not VHF or FM. The practical limits are revisit (a sparse constellation misses short-duration transmissions), geolocation accuracy (1–5 km CEP is not a street address), and the legal threshold (satellite data establishes presence, not intent or ownership).
Typical figures
| Frequency coverage | HF (3–30 MHz), VHF including FM broadcast (87.5–108 MHz); exact sub-bands depend on SDR configuration and tasking |
| Geolocation accuracy (VHF/FM) | 1–5 km CEP using TDOA/FDOA with cluster-flight architecture (HawkEye 360 published figures) |
| Geolocation accuracy (HF) | Typically tens of kilometres; sufficient for country-of-origin attribution, not transmitter-site pinpointing |
| Minimum detectable ERP (FM broadcast) | Approximately several hundred watts under favourable conditions; sub-100 W detection is not reliably achievable from LEO with current published systems |
| Revisit rate | Multiple passes per day over most latitudes with HawkEye 360 or Spire constellations; exact frequency depends on orbital geometry and constellation state |
| Dwell time per pass | Approximately 5–10 minutes over a fixed ground point per LEO pass |
| Weather sensitivity | None for VHF/FM; HF affected by ionospheric absorption, particularly at high latitudes and during geomagnetic disturbances |
| Latency (standard tasking) | 12–48 hours from pass to delivered analytic product |
| Archive depth | HawkEye 360 commercial archive from approximately 2019; Spire from approximately 2016 for selected bands |
| Delivery format | Power spectral density time series, geolocated signal detections (GeoJSON or shapefile), PDF regulatory evidence report |
Analytics Satellize can run
| Baseline spectral occupancy map | Wideband PSD aggregation across scheduled passes; comparison against ITU MIFR and national licensing database | GIS layer showing frequency occupancy by geographic cell, with licensed versus anomalous signal flags |
| Anomalous transmitter detection alert | Automated threshold detection on frequency, power, and geolocation deviation from licensed register | Timestamped alert with signal frequency, estimated location (CEP ellipse), and confidence score |
| Geolocation evidence package | TDOA/FDOA processing on multi-satellite cluster passes; uncertainty ellipse calculation | PDF report with geolocation plot, signal parameters, and pass metadata suitable for regulatory submission |
| Temporal transmission pattern analysis | Multi-pass time-series analysis to characterise on-air schedule and duty cycle of flagged transmitter | Transmission schedule chart showing active periods across a defined monitoring window |
| HF origin-country attribution | Skywave propagation modelling combined with orbital geolocation to constrain probable transmitter location to country or sub-regional level | Probability map of transmitter location with stated confidence intervals and propagation model assumptions |
| Comparative power anomaly assessment | Relative received-power ranking of co-channel or adjacent-channel signals within a geographic area to flag over-powered candidates | Ranked signal table with relative power index and recommended ground-inspection priority |
Who does the work
We can get this done for you. Satellize runs its own analyst desk and a strong science team. You do not buy a data feed and work out what it means; our people source the imagery, run the analysis described on this page, and hand you the answer with its confidence limits stated. Discuss this requirement.