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Outbyte Driver Updater FREEScan for outdated or missing drivers - takes under a minuteDriver Scan →Outbyte PC Repair FREEClear out junk files and repair common Windows errorsFree Scan →Drone swarms can reduce their reliance on GPS/GNSS by estimating motion and nearby aircraft from onboard sensing. They can also reduce their reliance on continuous messages by using local behaviors and estimated neighbor states. But those are separate capabilities: the available demonstrations do not establish reliable swarm operation when GNSS and inter-drone communications are both disrupted at once across realistic outdoor conditions.
What changes when GPS or communications fail?
GPS is part of the broader Global Navigation Satellite System (GNSS). Losing GNSS can remove a convenient source of global position, but it does not necessarily eliminate every way for a drone to estimate its motion or position relative to nearby aircraft. Losing communications is a different problem: aircraft may no longer exchange commands or state updates over a network.
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A swarm may therefore keep some local coordination after one source of information becomes unreliable, while still losing capabilities that depend on it. The key distinction is between estimating where aircraft are, exchanging those estimates, and deciding what to do next. A system that addresses one of these does not automatically solve the others.
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How can drones coordinate without dependable GNSS?
Without an external position reference, aircraft can use onboard sensing and observations of nearby agents to estimate relative motion and support behaviors such as flocking. Multi-robot state estimation can help maintain a mutually consistent picture of the agents’ states. This can support formation or group movement without requiring every aircraft to know its global GPS coordinates.
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A 2024 study by Jiří Horyna, Vít Krátký, Václav Pritzl, Tomáš Báča, Eliseo Ferrante, and Martin Saska describes decentralized cooperative flight in GNSS-denied, feature-poor environments without external localization and communication. The approach uses onboard mutual perception and flocking state feedback, with an enhanced multi-robot state-estimation strategy. The authors also warn that onboard localization can be unreliable in real environments, so relative estimation should not be mistaken for perfect or drift-free positioning.
The institutional record for the study says the proposed system was tested in complex real-world experiments under different conditions, including an interception-motivated task. That evidence applies to the paper’s system and experiments; it does not establish a general reliability rate for all swarms or environments.
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How can coordination continue when messages are missing?
One strategy is to make behavior less dependent on every aircraft receiving every update. Local rules can use onboard observations and recent estimates to guide movement, while a drone estimates states that might otherwise have arrived in a message. Horyna and colleagues describe a communication-less version of their approach that estimates such states to reduce dependence on unreliable networks.
“Communication-less” in this context is not proof that communication never matters. It describes a particular research approach to reducing reliance on explicit messages for coordination. The evidence does not show that arbitrary missions can continue unaffected after all links fail, or that the same behavior will remain safe and effective in every setting.
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What mesh networking can—and cannot—do
When radio links still work, a mesh can offer alternate paths for command, control, or data exchange. If one path becomes unavailable, information may be able to travel through other connected nodes or infrastructure. A mesh is therefore a resilience aid, not a guarantee: it cannot carry information across a fully disconnected network, and link quality can deteriorate with terrain, vegetation, or buildings.
A 2025 Michigan Department of Transportation deployment evaluated DSRC and C-V2X technologies in a short-range mesh framework for unmanned aircraft system (UAS) beyond-visual-line-of-sight operations. The report describes successful support for the operations tested and multimodal integration, while also reporting that terrain, vegetation, and building obstructions affected communications performance. It was a UAS communications deployment, not a demonstration of three-dimensional drone-swarm operation under jamming; the report recommends further swarm testing.
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How the approaches differ
| Approach | What it helps with | What the cited evidence establishes | Important limit |
|---|---|---|---|
| Onboard mutual perception and state estimation | Relative awareness and cooperative behavior when external GNSS localization is unavailable | Horyna and colleagues report real-world experiments with their proposed GNSS-denied approach in 2024 | The authors note that onboard localization may be unreliable in real environments |
| Local behavior with estimated neighbor state | Reducing dependence on explicit, continuous peer messages | The 2024 study describes a communication-less version that estimates states otherwise communicated | This does not establish that all coordination or mission requirements can be met without communications |
| DSRC and C-V2X mesh networking | Maintaining command, control, or data exchange along available network paths | Michigan DOT reports a 2025 UAS mesh deployment supporting the tested operations | Obstructions affected performance, and the report calls for more three-dimensional swarm testing |
What swarm demonstrations show about scale
DARPA’s 2017 Service Academies Swarm Challenge involved mixed fixed-wing and quad-rotor swarms in a 25-on-25 challenge. DARPA also reported that the number of aircraft pushed experimental networking infrastructure to its limits, making it harder to send commands and update tactics. The example illustrates how network capacity can become a coordination constraint as the number of agents rises.
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At the final field experiment for DARPA’s OFFSET program in 2021, the agency reported more than 300 combined air and ground platforms operating collaboratively across two integrators’ testbeds. The total was for air and ground systems together, not 300 drones. The experiment also included virtual agents and human-facing interfaces such as VR, AR, sketch tablets, and mobile phones. It demonstrates work on collaborative autonomy and human-swarm teaming, not the simultaneous loss of GNSS and inter-drone communications.
In DARPA’s 2021 account, OFFSET program manager Timothy Chung said: “We have demonstrated in the field that these swarm capabilities are rapidly nearing availability for future operations.” This was a statement about OFFSET’s demonstrated swarm capabilities, not a claim that swarms were proven to operate through both disruptions in the title.
What happens when both disruptions occur together?
The central uncertainty is the combination. The cited 2024 work addresses GNSS-denied cooperative flight and reduced reliance on explicit communication; the Michigan DOT report addresses UAS mesh communications; DARPA’s programs report swarm demonstrations at scale. Those sources cover related but distinct conditions. They do not establish reliable operation when GNSS and inter-drone communications are both disrupted at once across varied real-world environments.
No general published reliability percentage for that combined condition is established by these sources. The 25-on-25 and 300-plus counts describe different DARPA demonstrations and must not be combined into a performance claim about GNSS- and communications-denied flight.
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