现有的面阵场景下的频控阵(Frequency Diverse Array,FDA)MIMO雷达参数估计方法大多需要进行谱峰搜索,因此面临计算复杂度高、估计精度不够准确等困难.针对这一问题,提出了一种基于均匀面阵FDA-MIMO雷达的无网格参数估计方法.首先推导了角度和距离解耦的均匀面阵FDA-MIMO雷达模型,其次提出了适用于该模型的基于低秩矩阵重构的优化问题,并推导了基于交替投影的算法实现,以加快计算速度.最后通过仿真实验验证了所提算法在计算复杂度较低的同时具有较高的估计精度.
A gridless parameter estimation method for FDA-MIMO radar based on uniform planar array
Most existing methods for parameter estimation of frequency diverse array multiple input multiple output(FDA-MIMO)radar in planar array scenarios require spectral peak searching,thus they usually face difficulties like high computational complexity and inaccurate estimation accuracy.To address these challenges,a gridless parameter estimation method for FDA-MIMO radar based on uniform planar array(UPA)is proposed.Firstly,a UPA-based FDA-MIMO radar model with angle and range decoupling is derived.Secondly,an optimization problem based on low-rank matrix reconstruction is established for this model,and an algorithm implementation based on alternating projection is derived to speed up the calculation.Finally,simulation results show that the proposed method has high estimation accuracy with low computational complexity.
frequency diverse array multiple input multiple output(FDA-MIMO)radaruniform planar arraylow rank matrix reconstructionalternating projection
万方数据
维普
