"With radio frequency interference (RFI) threatening everything from civilian flights to military operations, GNSS interference intelligence is paramount to mitigating the fallout."
The aviation industry relies heavily on GNSS systems for its safety, operations, and efficiency. When GNSS is compromised through radio frequency interference (jamming or spoofing), it can negatively impact things like navigation and communications, putting anyone operating in or near the airspace at risk.
According to EUROCONTROL, a pan-European civil-military organization dedicated to supporting European aviation, instances of GNSS interference have been on a sharp rise since 2018. While most of this interference has occurred in and around conflict zones like the Baltic Sea and Eastern Mediterranean, instances of GNSS jamming and spoofing are increasing globally - affecting tens of thousands of civilian flights across Europe and abroad.
With radio frequency interference (RFI) threatening everything from civilian flights to military operations, GNSS interference intelligence is paramount to mitigating the fallout. One way to identify locations where GNSS jamming does or might occur is by monitoring and assessing ADS-B system parameters from past and current flights.
What is ADS-B?
Automatic Dependent Surveillance-Broadcast (ADS-B) is a surveillance technology used in aviation that determines an aircraft’s position in the airspace using satellite navigation or other sensors and communicates that in real time to ground stations, air traffic control (ATC), and other aircraft with ADS-B receivers.
ADS-B is performance-based, providing data on specific operating parameters to help monitor flight performance and navigation while operating in the air domain.
Still, one of the biggest advantages of ADS-B is its improved safety for civilian aircraft. Since both the pilot and ATC know the GNSS is working well and have a high level of situational awareness during a flight, the likelihood of air collisions or other operating errors is low.
ADS-B is composed of two primary services: ADS-B In and ADS-B Out.
ADS-B In
ADS-B In provides pilots and aircraft operators with weather and air traffic/position information sent directly to the cockpit through an ADS-B In receiver. This information is crucial for situational awareness and helps pilots avoid collisions or navigational errors in the airspace.
ADS-B Out
ADS-B Out is the component that sends an aircraft’s GNSS location, speed, altitude, horizontal position, aircraft identification information, and more to any ground station, satellite, or aircraft equipped with an ADS-B sensor.
These data are sent approximately 1-2 times per second following the aviation industry’s ADS-B regulations. When an ADS-B transmission is made to a ground station, the data is sent directly to ATC for flight operations and oversight.
Source: Spire Global (How Does ADS-B Work?)
Identifying Threats in the Airspace with ADS-B
ADS-B provides pilots and flight operators with up-to-date navigational information for situational awareness and data based on specific operating parameters to help identify poor GNSS equipment performance.
Since aircraft broadcast their GNSS position through ADS-B systems, monitoring ADS-B provides a clear and targeted method for identifying potential GNSS interference.
Over the past several years, ADS-B data parameters have been studied regarding GNSS interference events and are now used to help identify localized RFI. The more data points used, the higher the chance the strategy can accurately locate GNSS jamming or interference.
GNSS Transponder Malfunctions
ADS-B Out “drops” describe when an aircraft’s ADS-B system does not send ADS-B data to ground stations, satellites, or other aircraft. While an ADS-B Out drop does not necessarily signify GNSS interference, the event can be used to investigate further and determine if interference is occurring.
For example, some ADS-B Out drops only signify poor ADS-B transponder performance, while multiple ADS-B Out drops in the same location from numerous aircraft are often a good indicator of local radio frequency interference.
GNSS Jamming
The first thing to consider is that while all instances of GNSS jamming result in certain ADS-B parameters failing, not all failed ADS-B parameters signal GNSS jamming with 100% certainty.
When radio frequency interference is present, an aircraft's ADS-B Out may not broadcast certain data correctly. This can be seen with values in the operational datasets, such as horizontal and vertical positioning, which are used to investigate the ADS-B errors in the case of other failed parameters.
The Link Between ADS-B Performance and GNSS Interference
Two categories of ADS-B Out data are used to identify areas with potential GNSS jamming and to calculate the risk within a potential interference zone. Again, while not all failed parameters signal GNSS jamming, numerous instances of failed ADS-B parameters from multiple aircraft are often a good sign of interference.
ADS-B Parameters Used for GNSS Interference Intelligence
Navigation Accuracy Category Position (NACp)
NACp data provides an aircraft's estimated vertical and horizontal position uncertainty (EPU), sent in the operational status every 2.4-2.6 seconds. NACp anomalies occur when the aircraft's actual position does not fall within the estimated position 95% of the time and are considered a good indicator of when an aircraft’s GNSS transponder is malfunctioning or when a GNSS signal is being jammed.
Navigation Integrity Category (NIC)
NIC data indicates the horizontal containment radius around an aircraft, sent in the airborne position message every 0.4-0.6 seconds. NIC anomalies occur when the aircraft's position is not guaranteed, with a 99.999% probability, to be within the horizontal protection level of the containment radius. The bigger the containment radius, the smaller the probability percentage.
How Are NACp and NIC Used to Map Potential GNSS Jamming?
Since just one failed value (NACp or NIC) does not necessarily signify GNSS jamming, a correlation between two or more values can be used to determine the likelihood of localized jamming or interference.
One method studied at the University of Stanford used ADS-B data from ground stations alongside Machine Learning (ML) technology, described below. (This study used ADS-B parameter qualifications based on the FAA’s PAPR user guide, which can be found here.)
* Some research has been done using ADS-B parameters, but only a little, as existing challenges within the data make correlating GNSS interference difficult. The study described below employs ML to help circumvent the difficulties associated rather than relying on traditional mathematical models.
Study Methodology:
In this study, an initial alert was sent from rapid or prolonged NACp changes in ADS-B messages detected in terrestrial data stations.
NACp values range from 0-11, with higher values corresponding to better performance. Any value below 8 is flagged for inadequate performance, and a NACp value of 0 typically indicates no GNSS reception or jamming.
NIC values range from 0-11, with higher values indicating better GNSS performance. Under normal circumstances, an aircraft’s NIC will always be seven or higher (<0.2 nautical containment radius). A NIC value between 0-6 could represent moderate jamming or poor geometry, while a value of 0 indicates that the ADS-B system's setting is wrong or that the GNSS is severely affected by a jammer.
Researchers used NIC data as an input parameter to help validate NACp fluctuations as interference events. Since NACp data is broadcast less regularly than NIC data, NIC data ensures each NACp position has an associated quality indicator, helping validate concerns over NACp anomalies.
When both NIC and NACp did not meet standard operating parameters, a grid probability model was used to generate a GNSS jamming map for possible radio frequency interference (RFI) locations.
Study Results:
Using the ML model rather than traditional mathematical models, researchers improved the accuracy of RFI detection using ground-based ADS-B data correlation.
However, there is something that must not be overlooked...
Researchers tested the model with both real-life flight data and simulated edge cases. One of the simulated edge cases observed a dataset with unevenly distributed and missing data points. The edge case data was modeled around a lack of ground receiver coverage and/or mountains blocking the direct signal between the ground station and the observed aircraft.
The model generated a predicted bounding box that was smaller in size than the true bounding box, but its relative placement was close to the correct location of the region impacted by the jammer.
The result of the simulated edge case was that the model could identify the jammer-impacted region, but the lack of ground data lowered the confidence in the size of the bounding box.
The realistic problem is that the unobservable or missing data could be confused with the loss of GNSS signals caused by a jammer, so jammer confidence thresholds were ultimately lowered.
Satellite-Based ADS-B Monitoring Solves Ground Station Challenges
While terrestrial ADS-B ground stations, aircraft with ADS-B receivers, and other open-source information can provide a significant amount of ADS-B data for RFI detection and mapping, a few drawbacks must be considered in the search for better GNSS interference awareness.
The biggest concern about monitoring ADS-B with radar ground stations is their physical limitations.
Ground stations can only receive ADS-B signals from aircraft within range, and physical objects like mountains can interfere with signal reception - potentially confusing an operator as to whether or not interference is occurring. Further, ground surveillance stations are terrestrial, meaning signals cannot be obtained or used for RFI monitoring when a flight is operating over an open ocean without a ground station within range.
Simply put, ground stations alone do not provide the coverage or data collection capabilities for robust RFI detection; this is where ADS-B data collected by satellites comes into play.
Satellites can send ADS-B signals to ground receivers even when there is no direct link between an aircraft and an ADS-B-equipped ground station. Since satellites have near-global coverage, they minimize concerns about GNSS jamming over open water, in places with significant physical obstructions like mountain ranges, or even in conflict zones where numerous flights are not operating.
Space Services Using ADS-B Data for GNSS Jamming Intelligence
Space-based services that deploy satellites in low earth orbit (LEO) are the perfect tool to circumvent the limitations between ADS-B-equipped aircraft and their associated ground receivers. By passing ADS-B data from aircraft to satellites and then from satellites to ground receivers, near-global coverage is possible, and physical obstructions between aircraft and ground receivers become null.
Spire Global
Spire Global uses its constellation of ADS-B-equipped nanosatellites deployed across various low-earth orbits to collect and disseminate ADS-B information to ground stations for near-global RFI detection and mapping. Spire has a catalog of historical data, dating back 3+ years that can be used to analyze past and present interference zones - which are then calculated and mapped based on potential interference and risk.
Spire leverages AI and ML technologies, predictive modeling, and its proprietary satellite constellation to deconstruct raw ADS-B data (NIC/NACp) and turn it into actionable intelligence with the highest level of accuracy. It also pairs its ADS-B data with additional aircraft, flight, and weather information, which can be further deployed to satisfy needs beyond GNSS interference modeling.
Aistech Space
Aistech Space uses data from both space and ground-based receivers to track aircraft across the globe. It owns and operates a constellation of IoT- and ADS-B-equipped satellites operating in LEO, which help circumvent some of the ground-based tracking obstacles typically seen with ADS-B ground receivers. Their satellites differentiate between estimated and real flight paths and will continue searching for solutions that improve the coverage and accuracy of their ADS-B technologies.
While useful, the data is not necessarily applied to RFI detection, monitoring, and mapping.