多维度非圆结构化MIMO雷达参数估计方法研究

与传统的相控阵雷达相比，多输入多输出雷达能够获得信号的空域分集与波形分集增益，具有诸多优势。随着MIMO雷达所处的电磁环境日益复杂，使得MIMO雷达面临小样本、低信噪比以及阵列误差问题，导致传统的子空间技术类参数估计算法性能下降甚至失效。本项目通过同时利用MIMO雷达的多维度结构信息和张量结构信息，即多维度非圆结构信息，研究以高精度为目的，适应小样本、低信噪比和阵列误差背景下的MIMO雷达参数估计新方法与新理论。针对理想阵列条件下，研究基于张量分解理论的MIMO雷达非圆信号角度估计；针对阵列互耦误差条件下，研究基于信号多维度非圆结构信息的角度与互耦系数联合估计；针对阵列幅相误差条件下，研究基于信号多维度非圆结构信息的角度估计与幅相误差自校正。本项目的研究内容旨在解决小样本、低信噪比和阵列误差背景下的高精度参数估计问题。

Compared with traditional phased radar，Multiple-input multiple-output (MIMO) radar can obtain the spatial diversity gain and waveform diversity gain，which has a lot of advantages. In the increasingly complicated electromagnetism environment，MIMO radar has faced with the condition with small number of snapshot，lower SNR and array errors. And the subspace technique based parameter estimation algorithms has remarkable degraded performance and fail to work. Thus, this project focus on utilizing simultaneously the multi-dimensional structure information and noncircular structure information, i.e., multi-dimensional noncircularity structure information, to investigate high accurate parameter estimation algorithm in the presence of smaller number of snapshot, lower SNR, , and array errors. With the desired array structure, tensor decomposition based parameter estimation approach for noncircular sources is proposed; Then considering the mutual coupling in both the transmit and receive arrays, joint angle and mutual coupling estimation framework by using multi-dimensional noncircularity structure information is proposed. Finally, the angle estimation and gain phase error correction algorithm is proposed. This project aims at obtaining high arcuate parameter estimation in the presence of smaller number of snapshot, lower SNR, and array errors.