Dealing with jamming and spoofing – the growing importance of civilian GNSS resilience

Global Navigation Satellite Systems (GNSS) have come a long way since their inception with GPS for military applications in the 1970s. The turning point for civilian use occurred in 2000 when President Bill Clinton ordered the disabling of "Selective Availability," leading to a significant improvement in accuracy overnight. This decision opened up a plethora of new use cases for GNSS technology. Today, there are four primary global navigation satellite constellations: GPS (USA), Galileo (EU), BeiDou (China), and GLONASS (Russia), along with regional constellations like QZSS (Japan) and NavIC (India).

GNSS technology plays a crucial role in modern applications by providing reliable position, navigation, and timing (PNT) information to civilian systems. However, these signals are susceptible to degradation, disruption, or manipulation by various factors such as adverse weather conditions, solar activity, or deliberate attacks by malicious entities. Therefore, ensuring GNSS resilience is essential to maintaining accurate and timely data under challenging circumstances, with a focus on maintaining position fixes and promptly flagging unreliable data.

The repercussions of degraded or blocked GNSS signals can be severe, leading to significant economic losses or even endangering lives. Sectors such as fleet management, aviation, maritime shipping, emergency services, and critical infrastructure like telecommunications and energy grids heavily rely on GNSS for operations. Disruptions in GNSS signals can have far-reaching consequences, impacting various industries and potentially resulting in life-threatening situations in critical applications such as civil aviation, maritime navigation, emergency response, and autonomous driving systems.

GNSS systems face a myriad of threats, including jamming, spoofing, space weather, and geopolitical events. Jamming involves overpowering satellite signals with noise, rendering the service unusable. Spoofing, on the other hand, creates false signals to deceive receivers, leading to potentially dangerous outcomes such as misguiding vehicles or compromising timing systems. Space weather events like solar flares can disrupt satellite constellations and degrade GNSS signals, further highlighting the need for robust resilience measures.

One of the key reasons why GNSS resilience is crucial lies in the realm of real-time safety applications across various sectors such as aviation, maritime transport, and emergency services. For instance, in civil aviation, GNSS is extensively used for navigation, surveillance, and flight management throughout different flight phases. The technology enables precise tracking of flight paths, navigation over remote regions, and vertical guidance for safe takeoff and landing procedures. Any disruption in GNSS signals during aviation operations can lead to loss of situational awareness, erratic flight paths, and potential safety hazards for aircrews and passengers.

Why is GNSS resilience important?

The most significant risks from GNSS disruption occur when real-time safety data is generated from GNSS signals for aviation, vehicles, ships, and emergency services. For example, civil aviation uses GNSS extensively for navigation, surveillance, and flight management across almost all phases of flight. One use case for GNSS is providing route navigation without relying solely on ground-based navigation, enabling more direct routings, flexible airspace design, and fuel-efficient profiles. During departure, en route, and arrival, GNSS enables precise tracking of lateral flight paths, provides accurate navigation over oceans and remote regions, and enables vertical guidance and integrity for instrument-based landing and takeoff. When GNSS signals are unavailable or spoofed, crews can unexpectedly lose situational awareness, experience unstable flight paths, or encounter conflicting cockpit indications.

Large and high-speed vessels at sea use GNSS for coastal navigation, traffic separation, and navigation in constrained waters. When visibility is poor and traffic density is high, the loss or corruption of position data can translate into groundings, collisions, or failures during emergency manoeuvres.

GNSS is also being integrated into train control (for example, to maintain safe separation). Erroneous or unflagged positions can cause problems during movement, increasing the risk of overspeeding, collisions, or route conflicts.

Emergency services are increasingly using GNSS for dispatch systems, route planning, and emergency coordination to provide accurate, real-time positioning. Problems with GNSS can cause delays, misrouted resources, and confusion during fast-moving operations to tackle major fires, floods, or multi-vehicle accidents.

In automotive applications, automated road vehicles and advanced driver-assistance systems rely on GNSS, combined with other signals, to ensure accurate localisation. Untrustworthy signals can contribute to incorrect lane-level positioning or geofence violations.

GNSS resilience requires accuracy, integrity and continuity

Accuracy requirements differ between GNSS applications. For example, consumer navigation typically works with meter-level accuracy. Precision agriculture, urban planning and environmental monitoring often require decimetre- to centimetre-level performance. Further, aviation or autonomous systems often require both tight position bounds and strict integrity monitoring.

Accuracy determines how close the reported position is to the true position (for example, within a few meters, sub-meter or cm-level). However, accuracy alone is insufficient, as a system can provide a position value that looks correct even when the signal is degraded or spoofed. In this scenario, the reported position appears normal but is inaccurate, potentially posing a lethal risk in safety-critical applications.

Integrity ensures the reported position is reliable; if not, the system can issue a warning when the navigation system is unreliable, before the error becomes hazardous. In aviation, for example, the concern is not only whether the aircraft is within a few meters of the ideal track, but whether the navigation system can guarantee that any error is contained or an alarm is raised quickly enough.

Continuity describes whether the service maintains reliable performance throughout its operation, for example, during an aircraft instrument approach, a train movement, or a drone mission. A highly accurate system is still inadequate if it is interrupted and drops out halfway through a critical procedure.

Resilience using multi-constellation and multi-frequency GNSS

One way to make GNSS more resilient is to use receivers that support multiple constellations, enabling combinations of GPS, Galileo, GLONASS, and BeiDou signals, as well as regional systems where applicable. Multi-constellation systems boost geometric diversity, which in turn improves raw positioning accuracy and availability in real-world environments such as cities, mountains and high latitudes. The use of multiple constellations ensures that degradation, service interruption or local interference affecting one system does not immediately remove GNSS capability, because the receiver can fall back to signals from other constellations to maintain PNT.

Multi-frequency operation uses multiple bands from one or more constellations to boost immunity to interference and increase GNSS resilience. Interference is often caused by other local radios and RF devices and typically affects one GNSS frequency at a time. For instance, interference on one band, for example, L1, can be mitigated by tracking other bands, such as L2 or L5, to maintain positioning accuracy.

A key use of multiple frequencies is to compensate for ionospheric effects, a key source of error in single-frequency GNSS. Multi-frequency receivers deliver higher accuracy by removing first-order ionospheric errors, improving accuracy from several meters down to a meter or less. To do this, the delay of the same signal at two or more frequencies is compared, enabling receivers to estimate the ionospheric effect and adjust for it. [3]

The use of multiple frequencies also enables better noise mitigation and effective discrimination and rejection of multipath reflections in difficult environments. The L1 signal is particularly susceptible to multipath distortion, which can be mitigated by switching to another frequency. Various algorithms are available on the market to enable multipath resilience. Further, GNSS signals such as GPS L5, Galileo L1BC and Galileo E5-AltBoc are inherently more robust to multipath distortion.

The use of multiple frequencies also requires an attacker to degrade several GNSS signals consistently to spoof or jam the receiver. Multi-frequency receivers can compare range (distance to satellite) information from signals at different frequencies to detect anomalies. Integrity algorithms, derived and fine-tuned on real-world data and based on triple-band, multi-constellation technology, enable inter-constellation consistency checks and signal fallbacks. Inconsistencies can provide an early integrity warning, even before satellite augmentation is implemented.

Certain GNSS signals have built-in mechanisms for spoofing detection and prevention using cryptography and authentication. Open Service Navigation Message Authentication (OS-NMA) is an example of an anti-spoofing service on Galileo that uses the E1b signal. [4].

RAIM and satellite augmentation in receiver integrity

A receiver integrity monitoring concept that started with GPS and is also applicable to broader GNSS receivers, Receiver Autonomous Integrity Monitoring (RAIM) uses redundancy from multiple satellites to detect when one or more measurements are inconsistent with the rest. RAIM does not add new correction data from outside the receiver. Variations include Fault Detection (FD) RAIM, Fault Detection and Exclusion (FDE) RAIM, which provides fault detection and can exclude a compromised GNSS signal; Snapshot RAIM, which uses a current set of measurements; and Sequential RAIM, which uses both current and past measurements, which can improve detection over time. Typically, six satellites are needed to isolate and remove corrupt signals. Advanced RAIM (ARAIM) is an evolution of RAIM that extends the approach to multi-constellation and multi-frequency signals. ARAIM can be used with satellite-based augmentation to provide high-assurance positioning and integrity in critical applications.

In GNSS, satellite augmentation adds an external support layer of correction and integrity information to the raw signals from