Performance analysis of target parameters estimation using multiple widely separated antenna arrays

Target parameter estimation performance is investigated for a radar employing a set of widely separated transmitting and receiving antenna arrays. Cases with multiple extended targets are considered under two signal model assumptions: stochastic and deterministic. The general expressions for the corresponding Cramer-Rao lower bound (CRLB) and the asymptotic properties of the maximum-likelihood (ML) estimator are derived for a radar with Mt arrays of Lt transmitting elements and Mr arrays of Lr receiving elements for both types of signal models. It is shown that for an infinitely large product MtMr, and a finite Lr, the ML estimator is consistent and efficient under the stochastic model, while the deterministic model requires MtMr to be finite and Lr to be infinitely large in order to guarantee consistency and efficiency. Monte Carlo simulations further investigate the estimation performance of the proposed radar configuration in practical scenarios with finite MtMr and Lr, and a fixed total number of available receiving antenna elements, MrLr. The numerical results demonstrate that grouping receiving elements into properly sized arrays reduces the mean