共形FDA-MIMO雷达降维目标参数估计研究

Reduced-dimension Target Parameter Estimation For Conformal FDA-MIMO Radar

频控阵多输入多输出(FDA-MIMO)雷达是一种具有距离-角度-时间依赖性波束模式且能够提高自由度的系统。该文将可实现降低空气动力学对载体影响、附着在载体表面的共形阵列引入到FDA-MIMO雷达中。首先创建共形FDA-MIMO测量模型,推导参数估计的克拉默-拉奥下界(CRLB)。为了避免传统三维多重信号分类算法(3D-MUSIC)三维搜索,提出一种降维多信号分类(RD-MUSIC)算法实现目标参数估计。仿真结果表明,该算法与3D-MUSIC算法相比,估计精度有所下降,但计算复杂度显著降低。此外,与3D-MUSIC算法相比,该算法具有更好的多目标距离估计性能。

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.