Sanders Geophysics (SGL) and Ottawa's Carleton University are planning to fly a new purpose-developed unmanned air vehicle (UAV) equipped carrying magnetic anomaly detectors (MAD) during 2008 as part of plans to replace manned aircraft in very low level survey roles for the resources sector.
The new UAV, designated GeoSurv II, will be based on concepts under study for the three years at Carleton University for a new low cost, robust, all composite airframe.
Malcolm Imray, aviation manager at SGL says that while some UAVs are already being used in magnetic survey roles, lower air vehicle signatures are required to provide improved wide area data collection.
He told the Unmanned Vehicle Systems Canada conference in Montebello, Quebec, that market surveys carried out by the company indicate there is no airframe in existence that would meet the programmes proposed signature targets, necessitating development of a new vehicle.
Manufacture of a demonstrator prototype is planned to be carried out across the course of 2007. The pusher configuration airframe will be 3.8 m (12ft 7in) in length and have a 4.8m wingspan. The aircraft will have a 70kg (150lb) maximum take-off weight and will be powered by a UEL AR741 engine. To meet mission endurance requirements the UAV will deploy a parafoil after transiting to a survey area. The MAD payloads would be wingtip mounted
A typical survey mission would see the UAV flying at 30ft (10m) for 4h at 60kt (110km/h) to cover a standard survey area of 10mile2 (26km2). The aircraft is also required to be able to climb up to altitudes of 8,000ft (2,500m) to enable measurement of the aircraft's own signature without the influence of ground magnetics before commencement of surveys.
Parallel research, jointly funded using grants from the Ontario state government, will examine enhanced air vehicle autonomy, obstacle detection and avoidance, vacuum resin composite construction techniques, and development of aircraft actuators with extremely low magnetic signatures.
Carleton University flew prototype avionics in a converted model aeroplane during 2005 but is about to establish a full bench top development environment around a MicroPilot MP2028 autopilot. The bench top system is also likely to include the use of intelligent agents, with Agent Orientated Software's JACK suite identified as a candidate says Prof Paul Straznicky, project head at Carleton.
Sense and avoid capabilities for the UAV are to be based on a computer vision system which performs feature mapping against predefined obstacle classes. SGL and Carleton are flying a series of representative missions this month using manned aircraft to create a database of features for use in system development.
The initial test flights in 2008 will be carried out with the UAV being remotely operated says Straznicky, with spiral increments leading up to a fully autonomous capability. The UAV endurance is also expected to evolve to support missions of up to 8h.