On the Use of UAVs for Strapdown Airborne Gravimetry
Airborne gravimetry is a cost-effective technique to complement the gravity field information from satellite missions such as GRACE and, in the near future, GOCE. Measurements can be collected over regional areas in a relatively short time. Moreover, it is an especially useful method in remote areas and coastal water zones where terrestrial and ship-borne gravity measurements are difficult.
One drawback of airborne gravimetry is aircraft availability and the associated cost of flight time. If these problems can be reduced or minimised, airborne gravimetry can be made more accessible and cost-effective. A possible option discussed here is based on the use of Unmanned Autonomous Vehicles (UAVs).
The use of UAVs has increased in a large number of fields and is proving to be a viable and cost-effective option. However, the performance of UAVs is considerably different from regular fixed-wing aircraft and will have a significant impact on the performance of a gravimetry system. Also, due to the dimensions and operational requirements of spring gravimeter systems, these systems cannot be used inside UAVs.
This paper discusses how parameters, such as flight speed, endurance, and flight dynamics, can affect the determination of gravity anomalies and definition of the geoid using strapdown gravimetry systems on board of UAVs.
The study is limited to the use of the so-called Light UAVs which have a Maximum Take-Off Mass (MTOM) of less than 150 kg, since those can be relatively inexpensive. Some typical parameters used here for this range of UAVs are a cruise speed of 30 m/s, an endurance of several hours and a payload mass of several tens of kilograms.
First results, based on PSD (Power Spectral Density) analysis, indicate that, for a navigation grade inertial system, the use of UAVs can be an advantage in recovering the short wavelength (<5 km) information of the gravity field.
KeywordsGravity Field Gravity Disturbance Flight Dynamic Gravity Signal Airborne Gravimetry
Richard Deurloo is supported by a Ph.D. grant (SFRH/BD/25618/2005) from the Fundação para a Ciência e Tecnologia (FCT). This funding is greatly acknowledged.
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