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Random freezes, missing sound and display glitches usually trace back to one bad driver. Find and replace yours safely.Free scan · under a minuteDrone swarms can reduce their reliance on GPS/GNSS by using onboard sensing, observations of nearby aircraft, and distributed state estimation. They can also reduce reliance on continuous peer-to-peer messages by making local decisions from observations and estimated neighbor states. Those are separate capabilities, however: current cited evidence does not establish reliable swarm operation when GNSS and inter-drone communications are both disrupted at once across realistic outdoor conditions.
Why losing GPS and losing communications are different problems
GNSS provides positioning and timing references; communications carry information between aircraft or between aircraft and a human operator. Losing one does not automatically mean losing the other. A swarm might still exchange messages while GNSS is unavailable, or it might retain some navigation capability while links between drones fail.
That distinction matters because a shared map position and a shared understanding of neighboring drones are not the same thing. Onboard sensing and relative observations can help a drone estimate its motion and the positions of nearby agents without a global GPS coordinate for every aircraft. But estimated states can become uncertain, and the cited research explicitly warns that onboard localization may be unreliable in real environments.
How coordination can continue without a dependable GPS position
Onboard perception and relative state estimation
A drone can use onboard sensing to estimate its own state and observe nearby agents. Relative observations can support flocking or formation behavior without requiring every aircraft to know its global GPS position. Multi-robot state estimation can help the agents maintain a mutually consistent picture of their states.
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Horyna, Kratky, Pritzl, Baca, Ferrante, and Saska describe a decentralized approach for fast cooperative flight in GNSS-denied, feature-poor environments without external localization and communication. Their 2024 paper, “Fast Swarming of UAVs in GNSS-Denied Feature-Poor Environments Without Explicit Communication,” describes onboard mutual perception, flocking state feedback, and enhanced multi-robot state estimation. The authors report complex real-world experiments under different conditions, including an interception-motivated task; that evidence applies to their proposed system and experiments, not to every swarm or mission.
Local behavior when messages are missing
Instead of waiting for every drone to receive each update, a system can use local rules that act on onboard observations and recent state estimates. The 2024 study also describes a communication-less framework that estimates states that would otherwise be communicated. This can reduce dependence on an unreliable network, but it does not mean all coordination needs disappear: behavior still depends on the quality of sensing and estimation, and the evidence does not show that arbitrary swarm missions continue unaffected without messages.
What a mesh network can—and cannot—do
A mesh can provide alternate routes for command, control, or data while radio links remain available. It is a way to improve the odds that information gets through; it cannot guarantee connectivity when links are obstructed or unavailable.
A 2025 Michigan Department of Transportation report, “Unmanned Aircraft Systems Communication Mesh Test 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 tested operations and multimodal integration, while noting that terrain, vegetation, and buildings affected communications performance. It is 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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1Repair Windows errors before they cause bigger problems2Scan for outdated or missing drivers - takes under a minute3Clear out junk files and repair common Windows errorsWhat the demonstrations establish
| Evidence | What was demonstrated or reported | What it does not establish |
|---|---|---|
| GNSS-denied cooperative flight | Horyna et al. (2024) describe experiments with their decentralized approach in complex real-world conditions, including a feature-poor GNSS-denied setting. | Reliable performance for every environment or mission, or a general result for simultaneous GNSS and communications disruption. |
| UAS mesh deployment | Michigan DOT (2025) reports tested BVLOS operations using DSRC and C-V2X mesh infrastructure, with communications availability, latency, resilience, and multimodal coordination evaluated. | A swarm field test under GNSS denial and communications jamming; the report calls for more three-dimensional swarm testing. |
| 25-on-25 mixed swarm challenge | DARPA described mixed fixed-wing and quad-rotor swarms in its 2017 Service Academies Swarm Challenge. | Proof that large swarms can continue normally through simultaneous navigation and network denial. DARPA also reported that experimental networking limits made command and tactic updates harder. |
| 300+ mixed platforms | DARPA reported more than 300 combined air and ground platforms in collaborative operations at the final OFFSET field experiment in 2021. | 300 drones, or proof of operation under the exact dual-disruption conditions in this article. |
DARPA’s OFFSET program also illustrates the human-supervision side of swarm coordination. Its final field experiment used physical air and ground robots alongside virtual agents, with interfaces including VR, AR, sketch tablets, and mobile phones. Program manager Timothy Chung said in DARPA’s 2021 account that “We have demonstrated in the field that these swarm capabilities are rapidly nearing availability for future operations.” That statement describes OFFSET’s broader swarm capabilities; it is not a claim about simultaneous GNSS and communications denial.
What simultaneous GPS and communications disruption means in practice
If GNSS is lost but neighbor observations and messages remain usable, a swarm may be able to coordinate using relative sensing and shared estimates. If communications are degraded while localization remains available, local behaviors may reduce dependence on updates, while a mesh may offer alternate paths where links still exist. These examples describe different operating conditions, not a validated combined solution.
When both GNSS and inter-drone communications are disrupted, the available evidence does not establish how reliably a swarm will maintain formation, complete its task, or recover across varied outdoor environments. Nor does it provide a general reliability percentage for that condition. A large platform count in a demonstration, a GNSS-denied experiment, and a mesh-network deployment cannot be combined into such a performance claim.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to assess a claim about a resilient swarm
Look for evidence that tests the exact failure combination and mission being claimed. A result about GNSS denial alone says little about behavior when messages also disappear; a mesh result says little about navigation when GNSS is unavailable. Useful details include:
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- Localization: Does the system depend on GNSS, external localization, onboard sensing, or relative observations of nearby agents?
- Communication: Does it require explicit peer-to-peer messages, estimate missing neighbor states, or route information over a mesh? What behavior is expected when links fail?
- Environment: What sensing conditions are assumed, and how do occlusion, terrain, vegetation, or buildings affect perception and radio links?
- Evidence level: Is the claim based on simulation, controlled flight experiments, a field deployment, or a demonstration at scale? Are the test conditions the same as the claimed operating conditions?
- Supervision and recovery: What can a human operator still observe or command, and what is the documented response when localization or coordination becomes unreliable?
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