Resilient navigation for e-VTOL aircraft: countering GNSS jamming and spoofing in low-altitude urban airspace

Electric vertical take-off and landing (e-VTOL) aircraft are emerging as a core element of urban air mobility (UAM), promising reliable, zero-emission transport in dense cities. Safe operation depends on precise positioning and routing, particularly at low altitude where high-rise buildings, confined landing sites, and heavy traffic density compress safety margins. This makes navigation reliability a critical requirement.

Global Navigation Satellite Systems (GNSS) — GPS, Galileo, and GLONASS — remain the backbone of aviation positioning, yet they are vulnerable to radio frequency interference (RFI). Recent incidents involving commercial aircraft have shown that jamming and spoofing can disrupt GNSS signals, and these threats are not confined to high altitude. Interference, whether intentional or accidental, can degrade or falsify position data, eroding situational awareness and forcing unplanned rerouting, altitude changes, or loss of separation. In crowded urban airspace, the consequences are especially severe.

Current countermeasures rely largely on hybrid architectures that combine inertial navigation (INS/IRS) with radio altimetry and enhanced ground proximity warning. These help, but they fall short of the resilience and cybersecurity assurance that safe, scalable UAM will demand. There is a clear need for new methods, hardened equipment, and validated frameworks to keep e-VTOL navigation trustworthy under GNSS denial or degradation.

This Research Topic invites contributions that strengthen the resilience of e-VTOL navigation against GNSS jamming and spoofing in low-altitude urban environments. We welcome work spanning multi-sensor fusion, AI-driven interference detection, hardened receiver design, and the systems-engineering and cybersecurity frameworks needed to translate these into certifiable UAM operations. Contributions should demonstrate clear relevance to e-VTOL positioning, navigation, or timing (PNT) resilience.

We welcome original research, reviews, methods, and perspective articles on themes including, but not limited to:

- AI-driven detection of GNSS jamming and spoofing — machine learning, signal-processing, and deep-learning models for real-time anomaly detection in aviation and autonomous systems
- Resilient GNSS receiver and antenna architectures hardened against jamming and spoofing at low altitude
- Multi-sensor fusion combining GNSS with inertial navigation (INS/IRS), visual odometry, LiDAR, and radar altimetry for e-VTOL operations
- Hybrid navigation architectures for GNSS-denied or GNSS-degraded urban environments
- Cybersecurity frameworks and threat models for UAM navigation systems
- Real-time decision-making, rerouting, and separation assurance under GNSS disruption in dense urban airspace
- Certification, standards, and regulatory considerations for resilient e-VTOL navigation

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Data Report
• Editorial
• FAIR² Data
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• ... View all formats

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Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Data Report
• Editorial
• FAIR² Data
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Review
• Technology and Code

Keywords: GNSS, e-VTOL, Jamming, Spoofing, Flight safety, RFI

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.