Voyant Demonstrates Navigation Software for UK MOD
Voyant has successfully demonstrated its navigation software to the UK Ministry of Defence (MOD), marking an important step in the development of resilient Position, Navigation and Timing (PNT) capabilities for autonomous maritime systems operating in contested environments. In a real-life scenario, this capability would enable autonomous systems to continue navigating when satellite navigation has been lost or deliberately denied, supporting mission completion and the safe recovery of valuable assets.
The demonstration took place aboard a Kraken K3 Scout autonomous surface vessel in the littoral waters of the Solent. Operating in real time, Voyant's software used advanced particle filter algorithms to compare live radar imagery with pre-existing reference maps of the terrain to enable the vessel to determine its position without relying on Global Navigation Satellite Systems (GNSS).
The trial forms part of a wider MOD initiative to explore resilient technologies capable of supporting military operations in contested and congested GNSS-denied environments.
Modern military operations depend heavily on GNSS, including GPS, to provide PNT information for ships, aircraft, vehicles, missiles and autonomous platforms. However, satellite signals are increasingly vulnerable to jamming, spoofing and disruption, making resilient alternatives an increasingly important operational requirement.
The challenge is particularly acute in the littoral environment, where coastlines, changing terrain and dense infrastructure can naturally reduce satellite reception, even before adversaries actively seek to deny it. Maintaining accurate navigation in these complex environments is essential to ensuring autonomous and crewed platforms can continue to operate safely, effectively and with confidence.
Voyant's software addresses this challenge by fusing radar data with advanced probabilistic algorithms to estimate a vessel's position relative to its surroundings and provide an estimate of the uncertainty that is attributed to this estimate. Rather than relying on satellite signals, the system continually matches real-time sensor observations against known geographic features, providing trustworthy and resilient navigation even when GNSS is unavailable.
