A technique is developed for reducing the amount of aliasing in the spectra
l analysis of TIDI observations, by ingestion of ground-based data into the
satellite data set. A multi-dimensional (space-time) least squares fitting
approach is applied to the satellite and ground-based data to determine th
e aliasing spectra. The addition of ground-based data to the TIDI data set
reduces the aliased components in the aliasing spectrum. For example, at 20
degrees latitude, the combined ground-based and TIDI data set of a sampled
input semidiurnal (frequency of 2 days(-1)) signal with zonal wavenumber 2
results in a factor of 2 reduction in the amount of power aliasing into a
signal with zonal wavenumber 0 and frequency 0 days(-1).