Public GPS interference maps have become an essential awareness tool for tracking GNSS disruptions worldwide. Services like GPSJAM and GPSwise display interference data derived from aircraft broadcasts, helping aviation professionals and infrastructure operators understand where interference events occur. In 2025 alone, analysts documented over 1,500 flights affected by GPS interference daily, with more than 122,000 flights impacted in the first four months of the year, according to industry tracking.

Yet, these powerful visualization tools are frequently misunderstood. The same maps that raise awareness also create dangerous misconceptions when viewers assume they represent ground-level RF conditions or comprehensive threat coverage. This article explains what GNSS interference maps derived from Automatic Dependent Surveillance-Broadcast (ADS-B) data actually measure, why their limitations matter, and how critical infrastructure operators can avoid common interpretation errors that lead to complacency or misallocated resources.

How ADS-B Based GNSS Interference Detection Works

Understanding the data source is essential before interpreting any GPS interference map. Public interference maps rely on various ADS-B data sources, including networks like ADS-B Exchange and OpenSky Network. ADS-B is a surveillance technology where aircraft determine their position using GPS and periodically broadcast it to ground stations and other aircraft.

These maps primarily rely on navigation quality indicators embedded in ADS-B messages, specifically Navigation Integrity Category (NIC) and Navigation Accuracy Category for Position (NACp). When multiple aircraft in the same region simultaneously report degraded accuracy, the system flags a potential jamming zone. This method effectively detects jamming because interference causes measurable signal degradation that aircraft avionics report through these standard parameters.

Different services offer different detection capabilities. GPSJAM aggregates NIC/NACp indicators into hexagonal grids colored by severity, detecting jamming through signal degradation patterns. Their documentation explicitly states that colors represent the percentage of aircraft reporting low navigation accuracy within each hex. GPSwise, developed by SkAI Data Services, uses the OpenSky Network to detect both jamming (via NIC degradation) and spoofing (via trajectory anomalies such as position jumps or aircraft converging on false coordinates). This distinction matters: Jamming detection through signal degradation is well-established, while spoofing detection through trajectory analysis remains more experimental.

Three Common Misconceptions About GNSS Interference Maps

When context is missing, these valuable awareness tools create beliefs that are not just wrong but operationally dangerous. Based on conversations with infrastructure operators and GNSS professionals, three misconceptions recur most frequently:

Misconception 1: “This is Only an Aviation Problem.”

Because interference maps use aircraft as sensors, many observers frame GNSS disruption as exclusively an aviation issue. Pilots deal with it. Airlines reroute. The narrative stops there. This framing dramatically underestimates the threat. Aviation happens to provide a convenient, global measurement network. The aircraft is a sensor platform, not the only affected domain. The National Institute of Standards and Technology (NIST) has documented critical infrastructure dependencies on GPS timing across financial services, telecommunications and electric power sectors. When aircraft detect interference at altitude, the RF environment near the source may be affecting timing servers, cellular base stations, and grid monitoring systems that lack aviation-style navigation redundancy.

Misconception 2: ”We Are Always in Red, But Nothing Happens.”

Infrastructure operators in regions with persistent interference often observe their location marked red on these maps while their systems appear to function normally. The conclusion seems logical: either their systems are resilient, or the threat is exaggerated. Both conclusions can be wrong. The critical distinction is altitude. Aircraft observe a different RF environment than ground receivers. At cruise altitude (8,000 to 12,000 meters), an aircraft antenna has line-of-sight to interference sources over hundreds of kilometers. A ground-level timing receiver with a rooftop antenna may experience completely different conditions due to terrain, buildings and antenna orientation. GPSJAM’s own FAQ addresses this directly: “I live in a red hex and my phone GPS worked” is not a contradiction. It demonstrates that the map does not describe your personal ground-level environment.

Misconception 3: “Planes Aren’t Crashing, So There’s No Real Danger.”

Aviation has redundancy: inertial systems, distance measuring equipment, ground-based navaids, and trained crews. When GPS fails, aircraft can typically continue safely using backup navigation. This resilience creates a dangerous inference: If aviation handles it, the threat must be manageable. The logic inverts causality. If interference is powerful enough to degrade aircraft-reported GNSS integrity at altitude (where signals from the interference source have propagated through long distances and atmospheric attenuation), then the signal power near the source at ground level may be severe. A jammer affecting aircraft at 10 km altitude is projecting substantial RF power. Ground systems in the jammer’s vicinity, particularly those without aviation-grade redundancy, face potentially greater exposure.

What ADS-B Based Maps Cannot Show

Understanding the boundaries of ADS-B based detection helps operators assess what additional monitoring they need. These maps fundamentally cannot show several critical factors.

First, they cannot provide ground-level RF conditions at specific sites. A timing server, RTK base station, or telecom tower experiences local RF propagation that no aircraft flying overhead can measure.

Second, they cannot detect all interference types. Low-power, localized jammers may affect ground systems without triggering aircraft indicators. Academic research on ADS-B detection emphasizes that unknown aircraft installation details, antenna patterns, and fuselage attenuation all affect what aircraft can observe. Because of all these factors, aircraft-based monitoring can detect only high-power interference.

The temporal aggregation also matters. Most maps aggregate data over time windows, meaning a brief but intense interference event can paint a hex red even though GPS functioned normally for most of the day.

The Role of Ground-Based Monitoring

The gap between aircraft-based awareness and ground-level reality highlights a fundamental challenge. Unlike GNSS interference detection based on ADS-B data, ground-based sensors measure the actual RF environment at the location where protection matters.

This is where centralized ground-based monitoring becomes essential. While ADS-B data captures interference visible to aircraft at altitude, 99% of GNSS-dependent infrastructure operates at ground level. Timing servers in data centers, cellular base stations, power grid synchronization units, and financial trading systems all rely on GNSS signals received at ground level, where propagation conditions differ significantly from what aircraft experience at cruise altitude.

Ground-based monitoring sensors installed at critical infrastructure sites measure the actual RF environment where timing and positioning matter. They detect interference that may never reach aircraft antennas, including low-power jammers operating in urban environments or localized interference targeting specific facilities. A centralized monitoring architecture allows operators to correlate events across multiple sites, identify patterns, and respond to interference that aircraft-based systems simply cannot see.

How ADS-B Maps and Ground Monitoring Complement Each Other

ADS-B based maps and ground-level monitoring serve complementary rather than competing functions. A responsible approach treats them as layers in a complete awareness strategy.

ADS-B maps excel at regional awareness. They show where high-power GNSS disruption is occurring at scale, identify recurring hot zones, track the geographic spread of interference events, and build the case for resilience investment with visual evidence that non-specialists can understand.

Ground-level sensors provide site-specific truth. Only a sensor at your location measures the RF environment your systems experience. Ground sensors provide the detection latency, classification accuracy, and historical logging needed for operational response and post-incident analysis.

Correlating both creates complete situational awareness. When an ADS-B map shows your region as active, ground sensors can confirm or refute local impact. When ground sensors detect interference that does not appear on ADS-B maps, you have identified localized activity that aircraft-based systems miss. This correlation capability becomes particularly valuable for post-event analysis and developing mitigation strategies.

Conclusion

The proliferation of GNSS interference maps derived from ADS-B data represents a significant advance in threat awareness. With GPS jamming affecting hundreds of incidents daily in 2025, visibility into the problem has never been greater. But visibility is not protection, and awareness tools become dangerous when they create false confidence.

The core message for infrastructure operators is straightforward. ADS-B based maps show high-power GNSS disruption is occurring, where it recurs, and that the problem is growing. They do not show whether your specific ground-level site is affected, how your timing systems respond, or whether low-power interference is silently degrading your operations.

As GNSS interference transitions from a niche concern to an operational reality affecting aviation, telecom, finance, and energy sectors, the organizations that understand both what these maps show and what they hide will be best positioned to maintain resilient operations. The first step is recognizing that a red hex on a screen is a starting point for investigation, not a conclusion about your specific infrastructure. 

Author

Maksim Barodzka is the CEO and founder of GPSPATRON. Since 2012, he has been active in IT entrepreneurship, with a strong focus on embedded systems, real-time monitoring and RF/GNSS technologies. In 2018, he founded GPSPATRON, a company developing GNSS interference detection and classification systems designed to detect, analyze and support mitigation of sophisticated GNSS jamming and spoofing threats.

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