Parameter Estimation of Target With Angular Spread in the Near Field

Near-field target parameter estimation with multiple-input multiple-output (MIMO) systems has been extensively explored in existing literature. However, most methods are primarily effective only in passive or non-coherent scenario such as point scatters. In this paper, we consider a scenario where the near-field target expands in angular domain. Echoes originating from closely proximate directions within the angular spread are highly correlated, posing a significant challenge to existing models and algorithms, which may lead to biased estimations. To address the problem, we first build a model to describe the echo from the target with angular spread based on MIMO radar with only four parameters, including central range, central direction, angular spread and spinning angle. We then derive the Cramér-Rao bound (CRB) of parameter estimation in the proposed model and analyze the effect of angular spread and spinning angle on the estimation. An expanded-direction of arrival (DOA) network is proposed to estimate the four parameters in the model. With numerical simulations, we demonstrate the robustness of the model, analyze the limitations inherent in existing algorithms, and substantiate both the effectiveness and superiority of the proposed model and network.