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 L
_t
transmitting elements and Mr arrays of L
_r
receiving elements for both types of signal models. It is shown that for an infinitely large product M
_t
M
_r
, and a finite L
_r
, the ML estimator is consistent and efficient under the stochastic model, while the deterministic model requires M
_t
M
_r
to be finite and L
_r
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 M
_t
M
_r
and L
_r
, and a fixed total number of available receiving antenna elements, M
_r
L
_r
. The numerical results demonstrate that grouping receiving elements into properly sized arrays reduces the mean.