Recently, fast and reliable algorithms for the evaluation of spherical
harmonic expansions have been developed.
The corresponding sampling problem is the computation of Fourier coefficients
of a function from sampled values at scattered nodes.
We consider a least squares approximation to and an interpolation of given data.
Our main result is that the rate of convergence of the two proposed iterative
schemes depends only on the mesh norm and the separation distance of the
nodes.
In conjunction with the nonequispaced FFT on the sphere, the reconstruction of
$N^2$ Fourier coefficients from $M$ reasonably distributed samples is shown to
take $\cO(N^2 \log^2 N+M)$ floating point operations.
Numerical results support our theoretical findings.
Keywords:
approximation by spherical harmonics,
scattered data interpolation, iterative methods, nonequispaced FFT on the
sphere