基于辅助知识的低空风切变检测方法研究
发布时间：2019-01-27 20:13
【摘要】：机载气象雷达下视检测低空风切变时,有用的雷达信号往往被强杂波所掩盖,实现目标检测的第一步是杂波抑制。相较于传统雷达,相控阵雷达通过空时二维滤波,能够较好地抑制地杂波,可在强杂波背景下获得优越的目标检测性能。传统STAP(Space-time Adaptive Processing,STAP)技术一般是建立在均匀杂波环境下的,实际环境中杂波的非均匀特性导致了传统STAP方法的性能下降。随着高精度传感器的发展和对待检测目标特性研究的不断深入,将各种信息融入STAP技术以提高STAP处理能力的知识辅助型STAP(Knowledge Aided STAP,KA-STAP)越来越受到人们的关注。研究如何将各种辅助知识引入低空风切变检测,以提高机载气象雷达参数估计精度和检测能力具有重要的实际意义。首先,论文从相控阵机载气象雷达的接收数据模型入手,介绍了文章使用的风场及其雷达回波、地杂波的仿真思路。第二,论文根据RTCA DO-120准则,介绍了机载气象雷达风切变检测的主要流程,对其中的关键性步骤——风速估计、风速梯度估计、F因子计算进行了较为详细的介绍,并对风切变的检测流程进行了验证。第三,论文将地形数据、地表散射数据作为辅助知识,引入杂波训练样本挑选过程,实现了对非均匀环境下地杂波协方差矩阵的估计;同时将风场回波功率特征、风场谱宽、雷达工作参数等先验信息引入了风切变场的空时导向矢量建模中,建立了能够描述风切变场分布式气象目标特性的空时导向矢量。第四,论文以基于辅助知识的杂波协方差矩阵和风切变空时导向矢量为基础,提出了一种基于多通道联合自适应处理(Multiple Doppler Channels Joint Adaptive Processing,M-CAP)的,能够用于低空风切变场分布式气象目标风速估计的空时降维处理器结构。该处理器通过前置的加权多普勒滤波器将全空时杂波局部化为特定多普勒通道下的定向有源干扰,然后在空域逐多普勒通道进行自适应处理,实现风速估计,在保证估计精度的同时,使运算量大大减小。最后,论文提出了一种相控阵体制下基于压缩感知(Compressive Sensing,CS)的低空风切变谱矩估计方法,该方法根据风切变场的空时特点建立基于中心风速和速度谱宽的过冗余字典;然后使用压缩感知技术对风场回波进行重构,能够在脉冲较少条件下,获得较为精确的待检测单元风场风速及速度谱宽,同时讨论了利用中心速度和速度谱宽的非耦合特性的快速算法以及将谱宽作为先验知识进一步降低运算量的措施。
[Abstract]:When airborne weather radar detects wind shear at low altitude, useful radar signals are often masked by strong clutter. The first step to achieve target detection is clutter suppression. Compared with traditional radar, phased array radar can suppress ground clutter better by space-time two-dimensional filtering, and can obtain superior target detection performance in strong clutter background. The traditional STAP (Space-time Adaptive Processing,STAP) technique is generally based on the uniform clutter environment. The non-uniform characteristics of the clutter in the actual environment lead to the deterioration of the performance of the traditional STAP method. With the development of high-precision sensors and the research on the characteristics of target detection, more and more attention has been paid to integrating various kinds of information into STAP technology to improve the processing capability of STAP. It is of great practical significance to study how to introduce various auxiliary knowledge into low-altitude wind shear detection in order to improve the accuracy of airborne meteorological radar parameter estimation and detection ability. Firstly, starting with the receiving data model of phased array airborne meteorological radar, the paper introduces the wind field and the simulation idea of radar echo and ground clutter. Secondly, according to the RTCA DO-120 criterion, the paper introduces the main flow of airborne meteorological radar wind shear detection, and introduces the key steps of the process in detail: wind speed estimation, wind speed gradient estimation, F factor calculation. The flow of wind shear detection is verified. Thirdly, the terrain data and the surface scattering data are taken as the auxiliary knowledge, and the clutter training sample selection process is introduced to estimate the ground clutter covariance matrix in the non-uniform environment. At the same time, the prior information, such as wind echo power characteristics, wind field spectrum width and radar operating parameters, are introduced into the space-time guidance vector modeling of wind shear field, and the space-time guidance vector which can describe the distributed meteorological target characteristics of wind shear field is established. Fourthly, based on the clutter covariance matrix based on auxiliary knowledge and the wind shear space-time guidance vector, a multi-channel joint adaptive processing (Multiple Doppler Channels Joint Adaptive Processing,M-CAP) is proposed. Space-time dimension reduction processor architecture which can be used for wind speed estimation of distributed meteorological targets in low-altitude wind shear field. In this processor, the space-time clutter is localized into directional active interference under a specific Doppler channel through a predefined weighted Doppler filter, and then adaptive processing is carried out in the spatial domain by Doppler channel to realize wind speed estimation. At the same time, the calculation cost is greatly reduced. Finally, this paper proposes a low level wind shear spectral moment estimation method based on compressed sensing (Compressive Sensing,CS) in phased array system. According to the space-time characteristics of wind shear field, an overredundant dictionary based on center wind speed and velocity spectrum width is established. Then the compressed sensing technique is used to reconstruct the echo of the wind field, and the wind velocity and velocity spectrum width of the unit to be detected can be obtained under the condition of less pulse. At the same time, a fast algorithm using the characteristics of center velocity and velocity spectrum width is discussed, and the measures to further reduce the computation by using spectrum width as a priori knowledge are discussed.
【学位授予单位】：中国民航大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：V321.225
，
本文编号：2416655
[Abstract]:When airborne weather radar detects wind shear at low altitude, useful radar signals are often masked by strong clutter. The first step to achieve target detection is clutter suppression. Compared with traditional radar, phased array radar can suppress ground clutter better by space-time two-dimensional filtering, and can obtain superior target detection performance in strong clutter background. The traditional STAP (Space-time Adaptive Processing,STAP) technique is generally based on the uniform clutter environment. The non-uniform characteristics of the clutter in the actual environment lead to the deterioration of the performance of the traditional STAP method. With the development of high-precision sensors and the research on the characteristics of target detection, more and more attention has been paid to integrating various kinds of information into STAP technology to improve the processing capability of STAP. It is of great practical significance to study how to introduce various auxiliary knowledge into low-altitude wind shear detection in order to improve the accuracy of airborne meteorological radar parameter estimation and detection ability. Firstly, starting with the receiving data model of phased array airborne meteorological radar, the paper introduces the wind field and the simulation idea of radar echo and ground clutter. Secondly, according to the RTCA DO-120 criterion, the paper introduces the main flow of airborne meteorological radar wind shear detection, and introduces the key steps of the process in detail: wind speed estimation, wind speed gradient estimation, F factor calculation. The flow of wind shear detection is verified. Thirdly, the terrain data and the surface scattering data are taken as the auxiliary knowledge, and the clutter training sample selection process is introduced to estimate the ground clutter covariance matrix in the non-uniform environment. At the same time, the prior information, such as wind echo power characteristics, wind field spectrum width and radar operating parameters, are introduced into the space-time guidance vector modeling of wind shear field, and the space-time guidance vector which can describe the distributed meteorological target characteristics of wind shear field is established. Fourthly, based on the clutter covariance matrix based on auxiliary knowledge and the wind shear space-time guidance vector, a multi-channel joint adaptive processing (Multiple Doppler Channels Joint Adaptive Processing,M-CAP) is proposed. Space-time dimension reduction processor architecture which can be used for wind speed estimation of distributed meteorological targets in low-altitude wind shear field. In this processor, the space-time clutter is localized into directional active interference under a specific Doppler channel through a predefined weighted Doppler filter, and then adaptive processing is carried out in the spatial domain by Doppler channel to realize wind speed estimation. At the same time, the calculation cost is greatly reduced. Finally, this paper proposes a low level wind shear spectral moment estimation method based on compressed sensing (Compressive Sensing,CS) in phased array system. According to the space-time characteristics of wind shear field, an overredundant dictionary based on center wind speed and velocity spectrum width is established. Then the compressed sensing technique is used to reconstruct the echo of the wind field, and the wind velocity and velocity spectrum width of the unit to be detected can be obtained under the condition of less pulse. At the same time, a fast algorithm using the characteristics of center velocity and velocity spectrum width is discussed, and the measures to further reduce the computation by using spectrum width as a priori knowledge are discussed.
【学位授予单位】：中国民航大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：V321.225
，
本文编号：2416655
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