Parametric localisation of space-time distributed sources
Giuseppe A. Fabrizio, Douglas Andrew Gray, M.D. Turley · 2002
An explicit connection is made between the problem of jointly estimating the parameters of an autoregressive moving-average (ARMA) model which best fits the unbiased sample auto-correlation sequence (ACS) of the data in a least squares sense and the problem of estimating the parameters of superimposed exponentially damped complex sinusoids in additive noise. The mathematical equivalence between the two problems is exploited to derive a novel closed form technique which can be used to parametrically localise one or more space-time distributed sources received by a uniform linear array (ULA) in a computationally attractive manner. The new method is experimentally validated using experimental data from the receiving antenna array of the Jindalee over-the-horizon (OTH) radar located near Alice Springs in central Australia.