Along Track Interferometric Synthetic Aperture Radar (AT-InSAR) systems use more than one SAR antennas (typically
two), mounted on the same platform and displaced along the platform moving direction, to detect slow ground moving
targets. The phase of the ATI signal is related to the target motion parameters and may thus be used to estimate the radial
velocity. In this paper we approach the velocity estimation problem using statistical techniques based on the statistical
distribution of the measured interferometric phases. We analyze the radial velocity estimation with respect to ATI system
parameters, such as velocity values, the signal to clutter ratio (SCR), the clutter to noise ratio (CNR), considering a
deterministic target whose velocity is estimated using a Gaussian model. This model allows to take into account the lack
of knowledge of the target radar cross section (RCS) values and provides an analytical form for the interferometric phase
probability density function. Simulations results show that the adoption of Maximum Likelihood (ML) techniques, to
perform a joint estimation of velocity and SCR, and multi-channel configurations, to overcome ambiguities problems,
provide very good velocity estimation accuracy.
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