Maximum likelihood angle-frequency parameter estimation in unknown noise fields for low-elevation target tracking

In radar applications, the received echo signals reach the array elements via a multiplicity of paths even though there exist only one target. So, it is often relevant to estimate the direction and the Doppler frequency of each path ray. We apply in this paper a 2D extension of the Approximate Maximum Likelihood (AML) algorithm to estimate these parameters using a sensor array in an unknown additive noise field. We consider the case where the complex fading factor fluctuates from one Pulse Repetition Interval (PRI) to another one. Numerical simulations are provided to assess the performance of the approach, which is compared to the standard stochastic maximum likelihood derived for a white Gaussian noise.