Elements of statistical computing: numerical computation
Elements of statistical computing: numerical computation
Maximum Likelihood Estimation of Compound-Gaussian Clutter and Target Parameters
IEEE Transactions on Signal Processing
Identifiability in array processing models with vector-sensorapplications
IEEE Transactions on Signal Processing
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We develop a low-grazing angle (LGA) tracking method considering realistic physical and statistical effects, such as earth's curvature, vertical refractivity gradient of standard lower atmosphere, and non-Gaussian characteristics of sea-clutter. We employ a co-located multiple-input-multiple-output (MIMO) radar configuration using wideband orthogonal frequency division multiplexing (OFDM) signalling scheme. Apart from the frequency diversity provided by OFDM, we also exploit polarization to resolve the multipath signals by using polarization-sensitive transceivers. Thus, we can track the scattering coefficients of the target at different frequencies along with its position and velocity. We apply a sequential Monte Carlo method (particle filter) to track the target. Our numerical examples demonstrate the achieved performance improvements due to realistic physical modeling and OFDM MIMO configuration.