Low angle estimation: Models, methods, and bounds

In this work we study the performance of elevation estimators and lower bounds of the estimation error variance for a low angle target in a smooth sea scenario using an antenna array. The article is structured around some key assumptions on multipath knowledge, signal parameterization and noise covariance. We prove that the Cramer-Rao bound is highly dependent on the multipath model, while it is the same for the different signal parameterizations, and that it is independent of the noise covariance. The Cramer-Rao bound is sometimes too optimistic and not achievable. The tighter Barankin bound is derived to predict the threshold behavior seen at low SNR. Simulations show that the maximum likelihood methods are statistically efficient and achieve the theoretical lower bound on error variance, in the case of high enough SNR. Finally we show that the bounds can be used to design an improved array structure and study the influence of multiple frequencies. (C) 2000 Academic Press.