Calculating the precise geolocation of commercial unmanned aerial vehicles
Lead Participant:
DRONE DEFENCE SERVICES LTD
Abstract
Drones are set to transform industries of all types by optimising processes and reducing the cost of e.g. logistics and surveillance to near £zero. However, methods capable of tracking and increasing drone visibility need to be developed before commercial drones gain mainstream and legislative acceptance safely around our towns and cities.
Drone Defence herein aim to prove the feasibility of re-engineering the hardware/software of our existing RF sensor network. This innovation will allow our network sensors to act as differential GPS reference antennas; drone positioning accuracies down <50cm could be attainable.
For companies like e.g. Amazon, UPS and DHL knowing a drone's precise geolocation is critical to ensure: (1) more drones can fly closer together; (2) pin-point parcel drop-offs e.g. on a sheet of A4 paper rather than in someone's garden; (3) avoid critical infrastructure e.g. buildings and people; and (4) take the shortest route to each preplanned point coordinate, saving battery life, time and money. Finally, with the benefit of knowing their operational airspace is going to be protected and not at risk from unwanted threats.
Our proposed capability will allow the above vision to become a commercial reality and allow the creation of "sky ways", for the free movement of legal drones for logistical operations. Without our solution the e.g. Civil Aviation Authority (CAA) could restrict drone usage, possibly damaging if nor destroying this fledgling industry. We propose a viable alternative to support the industry and inhibit restrictive measures.
Our approach will use the latest telemetry methodology and in the near future will be augment with artificial intelligence and machine-learning capabilities; enabling autonomous drone tracking.
Our technology will offer end-users e.g. major cities, airports, prisons and the infrastructure sector to geofence "guard" their airspace, allowing robust vigilance to the growing network threat posed by commercial drones.
Drone Defence herein aim to prove the feasibility of re-engineering the hardware/software of our existing RF sensor network. This innovation will allow our network sensors to act as differential GPS reference antennas; drone positioning accuracies down <50cm could be attainable.
For companies like e.g. Amazon, UPS and DHL knowing a drone's precise geolocation is critical to ensure: (1) more drones can fly closer together; (2) pin-point parcel drop-offs e.g. on a sheet of A4 paper rather than in someone's garden; (3) avoid critical infrastructure e.g. buildings and people; and (4) take the shortest route to each preplanned point coordinate, saving battery life, time and money. Finally, with the benefit of knowing their operational airspace is going to be protected and not at risk from unwanted threats.
Our proposed capability will allow the above vision to become a commercial reality and allow the creation of "sky ways", for the free movement of legal drones for logistical operations. Without our solution the e.g. Civil Aviation Authority (CAA) could restrict drone usage, possibly damaging if nor destroying this fledgling industry. We propose a viable alternative to support the industry and inhibit restrictive measures.
Our approach will use the latest telemetry methodology and in the near future will be augment with artificial intelligence and machine-learning capabilities; enabling autonomous drone tracking.
Our technology will offer end-users e.g. major cities, airports, prisons and the infrastructure sector to geofence "guard" their airspace, allowing robust vigilance to the growing network threat posed by commercial drones.
Lead Participant | Project Cost | Grant Offer |
|---|---|---|
| DRONE DEFENCE SERVICES LTD | £88,614 | £ 62,030 |
People |
ORCID iD |
| Richard Gill (Project Manager) |