基于降秩STAP的低空风切变检测方法研究

发布时间：2018-03-17 04:11

本文选题：机载气象雷达　切入点：风速估计　出处：《中国民航大学》2017年硕士论文　论文类型：学位论文

【摘要】：飞机通过机载气象雷达来获取前方气象信息,未来相控阵体制将引入到机载气象雷达信号处理中,它的地杂波抑制能力更强,使得机载气象雷达对低空风切变的检测效果更好。空时自适应信号处理(Space Time Adaptive Processing,STAP)是相控阵体制雷达抑制地杂波的有效手段之一,但STAP需要足够的距离单元样本数来精准估计杂波协方差矩阵。实际环境中的种种非理想因素使得雷达接收数据中参考单元样本过少,从而严重影响STAP的性能。降秩STAP技术可以减少系统可调控权数,从而减少STAP技术中杂波协方差矩阵估计所需的训练样本数,因此研究如何将降秩STAP引入相控阵体制下低空风切变的检测,以提高机载气象雷达对低空风切变的检测能力就具有了重要意义。首先,论文对机载相控阵雷达的数据模型进行了介绍,分析了本文中所用的低空风切变回波信号、地杂波的模拟流程,并分析了前视阵体制下地杂波的距离依赖性。其次,针对机载前视阵雷达低空检测风切变时,训练样本数不足导致风场风速估计性能较差的问题,提出了一种基于改进EC-Capon法的低空风切变风速快速估计方法。该方法首先对特征分解后的杂波子空间准确估计,然后利用杂波子空间的正交补空间代替采样协方差矩阵求逆(Sampling matrix inversion,SMI)权矢量,利用特征对消的子空间白化法抑制地杂波,在Capon准则下求取权矢量实现对风场风速的有效估计。最后,针对无参考单元的情况下,提出了一种基于多级维纳滤波器的风速估计方法。本方法引入了风切变场的空时导向矢量建模,在不估计待测单元杂波协方差矩阵的前提下对待测单元数据直接降维处理,来实现低空风切变的风场速度的有效估计。
[Abstract]:The future phased array system will be introduced to the airborne meteorological radar signal processing, and its ground clutter suppression ability will be stronger. It makes airborne weather radar detect wind shear at low altitude better. Space-time adaptive signal processing (Space-Time Time processing) is one of the effective methods to suppress ground clutter by phased array radar. But STAP needs enough distance unit samples to estimate the clutter covariance matrix accurately. Thus, the performance of STAP is seriously affected. The reduced rank STAP technique can reduce the adjustable weights of the system, and thus reduce the number of training samples needed for estimating the clutter covariance matrix in STAP technology. Therefore, it is of great significance to study how to introduce reduced rank STAP into low-altitude wind shear detection under phased array system in order to improve the detection ability of airborne weather radar for low-altitude wind shear. This paper introduces the data model of airborne phased array radar, analyzes the simulation flow of the low altitude wind shear echo signal and ground clutter used in this paper, and analyzes the range dependence of the ground clutter under the forward view array system. When airborne foresight radar detects wind shear at low altitude, the insufficient number of training samples leads to poor performance of wind field wind speed estimation. A fast wind speed estimation method based on improved EC-Capon method for wind shear velocity at low altitude is proposed. Firstly, the clutter subspace is accurately estimated by this method. Then the orthogonal complement space of the clutter subspace is used instead of the sampling covariance matrix to calculate the inverse Sampling matrix inversion (Smi) weight vector, and the subspace whitening method of characteristic cancellation is used to suppress the ground clutter. The weight vector is obtained under the Capon criterion to estimate the wind speed of wind field effectively. Finally, in the case of no reference unit, A wind speed estimation method based on multistage Wiener filter is proposed, in which the space-time guided vector modeling of wind shear field is introduced, and the dimensionality reduction of the measured unit data is obtained without estimating the clutter covariance matrix of the unit under test. To realize the efficient estimation of wind field velocity of low level wind shear.
【学位授予单位】：中国民航大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：V321.225;V243.2

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