Reduced-dimension Target Parameter Estimation For Conformal FDA-MIMO Radar; [共形FDA-MIMO雷达降维目标参数估计研究]

Frequency Diverse Array (FDA) Multiple-Input Multiple-Output (MIMO) radar equipped with a FDA can possess beam patterns that are dependent on range, angle, and time, and it can increase the degree of freedom. This paper introduces a conformal array attached to the surface of the carrier, the array can reduce the aerodynamic impact on the carrier and reduce the cross section of the FDA-MIMO radar. First, the conformal FDA-MIMO measurement model is formulated, and a Cramér-Rao Lower Bound (CRLB) is derived to evaluate the parameter estimation performance. To avoid the three-dimensional search of the traditional three-dimensional MUltiple SIgnal Classification (3D-MUSIC) algorithm, a Reduced-Dimension MUltiple SIgnal Classification (RD-MUSIC) algorithm is proposed for parameter estimation. The simulation results demonstrate that the proposed algorithm has a slightly lower estimation accuracy than the 3D-MUSIC algorithm but a much lower computational complexity. In addition, the proposed algorithm has better range estimation performance for multiple targets than the 3D-MUSIC algorithm. © 2021 Institute of Electronics Chinese Academy of Sciences. All rights reserved.