基于SVD-TLS的EES-MIMO雷达电磁环境感知算法

为提高EES\|MIMO(Electromagnetic Environmental Sensory\|Multiple\|Input Multiple-Output)雷达在复杂电磁环境下测量精度和工作可靠性, 提出了一种新的基于整体最小二乘（TLS: Total Least Squares）方法与奇异值分解（SVD: Singular Value Decomposition）的电磁环境感知算法。SVD-TLS算法首先利用了互谱AR（Auto Regressive）模型参数估计, 然后考虑其互相关函数矩阵中的估计误差扰动, 并采用同时考虑方程右端互相关函数向量中估计误差扰动的TLS方法予以实现。仿真实验结果表明, 该算法具有良好的谱估计性能, 可较准确地感知环境中杂波所处的频段, 从而为EES-MIMO雷达利用剩余“干净”频带收发波形提供了可靠保证。

Method of Electromagnetic Environmental Sensory for EES-MIMO Radar Based on SVD-TLS

Effectively detecting the band frequency and power of airspace interference and cluster is the prerequisite for improving the accuracy and reliability of EES(Electromagnetic Environmental Sensory) and MIMO(Multiple-Input Multiple-Output) radar. This paper presents a new electromagnetic environment percep
tion algorithm based on TLS(Total Least Squares) and SVD(Singular ValueDecomposition). TLS-SVD algorithm uses cross\|spectrum AR(Auto Regressive) model estimation parameters and considers the disturbance estimation error of cross-correlation function matrix, then takes into account the TLS perturbation method for vectorerror estimate on the equation side so the cross-correlation function can be realized. The simulation results show that the proposed algorithm has a good performance of spectral estimation. It can sense the clutter band of the environment accurately, and provide favorable guarantee for sending and receiving waveform of the EES-MIMO radar using the remaining “clean” band.