Tactical military SATCOM uplink band occupancy monitoring
Space-based RF monitoring of the 292–317 MHz UHF MILSATCOM uplink band can characterise spectrum occupancy, flag unauthorised emitters and locate interference sources, without decoding a single protected message.
Sensors
- HawkEye 360 cluster satellites: Three-satellite formation flying in LEO at roughly 575 km altitude, using time-difference-of-arrival and frequency-difference-of-arrival (TDOA/FDOA) to geolocate emitters. Published geolocation accuracy is cited by HawkEye 360 as typically better than 1 km CEP under good geometry. Covers VHF and UHF bands including the 225–512 MHz military band.
- Spire LEMUR-2: Multi-mission LEO constellation of over 100 satellites carrying RF payload alongside GNSS-RO sensors. Capable of passive RF signal detection and spectrum sensing across a broad frequency range. Revisit is frequent but irregular, depending on orbital geometry over the target area; Spire publishes revisit statistics by latitude band.
- US DoD UHF Follow-On (UFO) satellite system: A constellation of GEO satellites providing UHF MILSATCOM service in the 292–317 MHz uplink band and 243–270 MHz downlink band. Publicly documented by the US DoD and NRL. Not a monitoring sensor, but the primary host infrastructure whose uplink band is the subject of occupancy monitoring.
- Advanced Extremely High Frequency (AEHF) system: US DoD GEO MILSATCOM system, publicly documented by the Air Force Space Command and GAO. AEHF operates in EHF (44 GHz uplink, 20 GHz downlink) rather than UHF, but its published programme documentation provides context for understanding the wider MILSATCOM architecture and the continued reliance on UHF terminals for legacy interoperability.
Why UHF uplinks remain the most monitored slice of military spectrum
The 292–317 MHz UHF uplink band is, by any measure, crowded. Decades of fielded terminals, allied interoperability requirements and the sheer cost of replacing legacy equipment mean that UHF MILSATCOM remains the primary tactical satellite link for a large fraction of ground, maritime and airborne military users worldwide. The US DoD's UFO constellation, documented extensively in public GAO and Congressional Budget Office reports, has served this band since the 1990s. That longevity is both a strategic asset and a spectrum management headache.
Because the band is shared, internationally coordinated and used by multiple allied nations under ITU Article 9 coordination procedures, any uncoordinated emitter, whether a malfunctioning terminal, a third-party commercial user operating without authorisation, or a deliberate interferer, affects operational communications. Space-based monitoring exists precisely to answer a question that ground-based spectrum managers cannot easily answer from a single vantage point: who is transmitting, from where, and with what duty cycle?
What a LEO cluster actually measures, and what it cannot
A formation of three LEO satellites separated by tens of kilometres can measure the time at which a UHF signal arrives at each spacecraft. The differences in those arrival times, combined with the Doppler frequency shifts caused by each satellite's velocity relative to the emitter, allow a TDOA/FDOA calculation that places the emitter on the ground. HawkEye 360 has published geolocation accuracy figures in the sub-kilometre CEP range under favourable geometry, though accuracy degrades when satellite elevation angles are low, when the emitter is near the edge of the formation's baseline, or when multiple emitters occupy the same frequency simultaneously.
The hard limit is content. A LEO RF monitoring payload receives the uplink signal as a radio wave. It can characterise centre frequency, bandwidth, pulse timing, modulation class and signal power. It cannot decrypt protected traffic, and it cannot resolve individual users when two terminals transmit on the same frequency from locations that produce similar TDOA signatures. Dense signal environments, common in joint exercises or contested theatres, produce ambiguity that no amount of signal processing entirely eliminates. Honest spectrum monitoring products acknowledge this; attribution to a specific terminal type or national operator requires corroborating intelligence, not just RF geometry.
Occupancy characterisation: reading the band's daily rhythm
Spectrum occupancy in the UHF MILSATCOM uplink band is not static. Published studies in journals such as IEEE Transactions on Aerospace and Electronic Systems have documented that military UHF bands exhibit strong temporal patterns tied to operational schedules, exercise cycles and geographic activity. A monitoring programme that accumulates passes over weeks or months builds a baseline occupancy model: which frequency sub-bands are active at which times of day, which geographic regions generate the most uplink energy, and what the typical signal-to-noise ratio looks like under normal conditions.
Deviations from that baseline are the product of interest. A new emitter appearing in a sub-band that has historically been quiet, a sudden increase in duty cycle over a specific region, or a signal whose modulation characteristics do not match the waveform families associated with known terminal types, each of these is a candidate anomaly. The monitoring system flags it; a human analyst determines whether it warrants further investigation. The system does not make attribution decisions autonomously, and responsible product design makes that separation explicit.
Interference events: geometry helps, but does not always close the case
Uplink interference into GEO MILSATCOM transponders is a documented and recurring problem. The ITU and US DoD have both published accounts of interference events caused by mispointed terminals, equipment faults and deliberate jamming. A LEO monitoring pass that captures an anomalous signal can, in principle, geolocate it to within roughly 1 km CEP and cross-reference that position against known terminal locations, vessel AIS tracks or facility databases.
In practice, several factors complicate closure. A single pass may last only a few minutes over a given area. If the interfering emitter transmits intermittently, the probability of intercept during any single pass is low; a denser constellation or a longer dwell time improves it. GEO-based TDOA using two co-located or adjacent GEO payloads offers a complementary approach with persistent coverage but typically coarser geolocation than a well-separated LEO cluster. The two methods are more complementary than competing, and a rigorous monitoring architecture uses both where available.
Sovereign programmes and the question of who owns the data
A government operating UHF MILSATCOM terminals has a legitimate interest in knowing the occupancy state of the band it depends on, independent of any allied spectrum management authority. That interest is particularly acute for smaller defence establishments that lack organic signals intelligence assets. Commissioning a space-based RF monitoring programme provides persistent, sovereign visibility into band health without requiring access to classified sensor networks.
Satellize structures analytics programmes for exactly this kind of client: a government that needs a defensible, independently sourced picture of its electromagnetic operating environment. The Tonga crop-estimation programme is a different domain, but the underlying architecture, combining open-access satellite data with commercial tasking on client licence, applies equally to RF monitoring. The analytics output is owned by the client, processed to their classification requirements, and delivered in formats compatible with existing spectrum management workflows. A brief scoping call with Satellize's RF analytics team is the right first step for any defence ministry assessing whether a monitoring programme is feasible within their budget and legal framework.
Typical figures
| Frequency coverage (monitoring payload) | VHF/UHF, broadly 100–6000 MHz depending on payload; UHF MILSATCOM uplink band 292–317 MHz within this range (HawkEye 360 published band coverage) |
| Geolocation accuracy (TDOA/FDOA, LEO cluster) | Typically better than 1 km CEP under good geometry; degrades at low elevation angles and in dense multi-emitter environments (HawkEye 360 published figures) |
| Revisit rate over a fixed point (LEO cluster) | Variable; a single three-satellite cluster provides multiple passes per day at mid-latitudes, but each pass window over a target is typically 3–8 minutes |
| Minimum detectable signal | Not publicly specified in absolute terms; detection probability depends on emitter EIRP, path loss at 300 MHz from ground to ~575 km altitude, and receiver noise figure |
| Latency from collection to product | Hours to sub-day for commercial RF monitoring services; near-real-time alerting architectures exist but depend on ground station contact frequency |
| Spectral resolution | Sufficient to resolve individual UHF MILSATCOM sub-channels (25 kHz channel spacing typical in this band); exact figure not publicly specified by sensor operators |
| Archive depth | HawkEye 360 operational since 2018; Spire LEMUR-2 RF payloads operational since approximately 2019; multi-year historical baselines available |
| Delivery formats | Geolocated emitter reports (CSV, GeoJSON, shapefile), spectrum occupancy time series, alert feeds via API; specific formats by agreement with sensor operator |
| Content decryption | Not possible. Monitoring is limited to signal presence, frequency, modulation class, timing and geolocation. Traffic content is inaccessible. |
Analytics Satellize can run
| Band occupancy baseline model | Statistical aggregation of signal-present/absent observations across frequency sub-bands and time-of-day bins, derived from accumulated LEO monitoring passes | Monthly occupancy report with per-sub-band duty cycle statistics and geographic heat map of uplink activity, delivered as PDF and GeoJSON |
| Anomalous emitter alert | Deviation detection against established occupancy baseline; signals outside expected frequency, timing or geographic parameters flagged for analyst review | Near-real-time alert feed (API or email) with geolocated emitter report, signal characteristics summary and confidence rating |
| Interference event geolocation report | TDOA/FDOA geolocation using LEO cluster pass data; cross-referenced against known terminal locations and vessel position databases where available | Single-event PDF report with geolocation estimate, uncertainty ellipse, signal parameters and timeline of detection |
| Modulation class characterisation | Automatic modulation classification applied to captured signal samples; comparison against published waveform families associated with known MILSATCOM terminal types | Signal classification table appended to occupancy or event reports; unknown waveforms flagged separately for specialist review |
| Temporal activity pattern analysis | Time-series analysis of emitter activity over weeks to months; identification of periodic patterns consistent with exercise cycles, operational schedules or persistent unauthorised use | Quarterly trend report with annotated activity timeline and comparison against prior periods |
| Multi-source interference correlation | Fusion of LEO RF geolocation data with GEO-based interference reports (where client has access) and AIS/vessel position data to narrow emitter attribution | Correlated event dossier with ranked candidate emitter locations and supporting evidence summary |
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.