This invention discloses a
Bayesian inversion extraction method for the equilibrium
signal of wide-span
altimeter data. The method involves acquiring and preprocessing
sea surface height anomaly sequences from
radar interferometers and
nadir altimeters. A normalized sine
square window function is applied for windowing, and multidimensional spatial averaging is used to estimate the one-dimensional
wavenumber power spectrum. A piecewise power law-based equilibrium
signal spectrum model and a
noise spectrum model constrained by dynamic
sea state are constructed, and the set of spectral parameters is extracted through logarithmic domain weighted
least squares fitting. A set of spatial
covariance matrices is constructed using cosine integral transform and Abelian forward and inverse transforms. A
graphics processor is scheduled to perform batch
matrix decomposition and singular fault-tolerant regularized inversion to solve for the posterior
mean vector and posterior
covariance matrix of the target equilibrium
signal. Window fusion and
index mapping are applied to fill the gaps in
nadir observations. Geostrophic dynamics parameters are calculated,
uncertainty quantification is performed based on the linear error propagation law, and the
knowledge base is updated based on the exponential
moving average algorithm. This invention achieves suppression of observation
noise and physical filling of observation gaps, improving the adaptability of the inversion
system to environmental changes while preserving non-
Gaussian dynamic characteristics.