Potential-Field Estimation Using Scalar and Vector Slepian Functions at Satellite Altitude

Alain Plattner () and Frederik J. Simons ()
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Alain Plattner: Princeton University, Department of Geosciences
Frederik J. Simons: Princeton University, Department of Geosciences

A chapter in Handbook of Geomathematics, 2015, pp 2003-2055 from Springer

Abstract: Abstract In the last few decades, a series of increasingly sophisticated satellite missions has brought us gravity and magnetometry data of ever improving quality. To make optimal use of this rich source of information on the structure of the Earth and other celestial bodies, our computational algorithms should be well matched to the specific properties of the data. In particular, inversion methods require specialized adaptation if the data are only locally available, if their quality varies spatially, or if we are interested in model recovery only for a specific spatial region. Here, we present two approaches to estimate potential fields on a spherical Earth, from gradient data collected at satellite altitude. Our context is that of the estimation of the gravitational or magnetic potential from vector-valued measurements. Both of our approaches utilize spherical Slepian functions to produce an approximation of local data at satellite altitude, which is subsequently transformed to the Earth’s spherical reference surface. The first approach is designed for radial-component data only and uses scalar Slepian functions. The second approach uses all three components of the gradient data and incorporates a new type of vectorial spherical Slepian functions that we introduce in this chapter.

Keywords: Slepian Functions; Satellite Altitude; Potential Field Approximation; Gradient Data; Chapter Scalars (search for similar items in EconPapers)
Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-54551-1_64

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DOI: 10.1007/978-3-642-54551-1_64

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