机载气象雷达信号处理若干关键技术研究
发布时间：2018-07-26 13:29
【摘要】：机载气象雷达是民航飞机上强制安装的机载电子设备，相当于飞机的“双眼”，可实时地探测飞行路径上存在的暴雨、湍流和风切变区域，给飞行员提供气象预警和安全的飞行路径。机载气象雷达对气象目标的探测是经过一系列复杂的信号和数据处理过程实现的，信号处理单元是决定机载气象雷达系统性能的重要部件。论文针对机载气象雷达信号处理若干关键技术进行了研究，主要工作总结如下。 1.论文比较了两种常见的仿真方法，基于回波统计特性和基于气象目标微物理特性的方法，并提出了一种结合机载快速存取记录器数据的全飞行阶段机载气象雷达回波仿真方案。 2.机载气象雷达是通过对回波的多普勒处理实现雨区探测、湍流和风切变的检测的,即估计回波的三个谱矩：功率、平均多普勒频率和谱宽。现今气象雷达系统中广泛采用的是非参数化的脉冲对方法，但不适用于信噪比低的情况和多高斯谱叠加的情况。论文充分利用气象雷达回波服从高斯谱这一特性，构造参数化的估计模型解决这一问题。首先，建立了回波的频谱、自相关函数和协方差矩阵的数学模型。针对低信噪比时的谱矩估计，论文在分析协方差矩阵特性的基础上，推广了正弦信号谱估计中的子空间和Capon方法，提出了三种参数化谱矩估计方法，通过在谱宽和平均频率上的二维搜索来得到估计值。针对多高斯谱混合时的谱矩估计，论文基于最小二乘拟合思想构造代价函数，提出了基于频谱和自相关函数拟合的谱矩估计方法，求解时通过循环优化思想解决多高斯谱回波混合时的谱矩估计问题。最后，通过蒙特卡罗仿真实验对方法性能进行验证。论文还提出了谱矩估计的快速计算方法，将估计时的二维搜索转化为两个一维搜索，可降低运算量。 3.地杂波是对机载气象雷达检测目标最大的影响因素。论文分析了气象目标回波和地杂波在频域的特征，提出了基于谱宽的地杂波抑制方法。利用实际数据进行了处理，并从抑制后的回波强度和频谱特性变化上分析了算法的性能，分析证明提出的方法能够有效抑制地杂波。
[Abstract]:Airborne weather radar is a compulsory installation of airborne electronic equipment on civil aviation aircraft, equivalent to the "eyes" of the aircraft, which can detect the rainstorm, turbulence and windshear areas in the flight path in real time. Provide pilots with weather warning and safe flight paths. The detection of meteorological targets by airborne meteorological radar is realized through a series of complex signal and data processing processes. Signal processing unit is an important component to determine the performance of airborne meteorological radar system. Some key technologies of airborne meteorological radar signal processing are studied in this paper. The main work is summarized as follows. 1. In this paper, two common simulation methods are compared, one is based on echo statistics and the other is based on the microphysical characteristics of meteorological target. A simulation scheme of airborne meteorological radar echo in the whole flight phase combining with airborne fast access recorder data is proposed. 2. Airborne weather radar detects rain area turbulence and wind shear by Doppler processing of echo namely estimating three spectral moments of echo: power average Doppler frequency and spectrum width. The non-parameterized pulse pair method is widely used in meteorological radar systems, but it is not suitable for the cases of low signal-to-noise ratio (SNR) and multi-Gao Si spectrum superposition. In this paper, a parameterized estimation model is constructed to solve this problem by making full use of the characteristic of meteorological radar echo from Gao Si spectrum. Firstly, the mathematical models of spectrum, autocorrelation function and covariance matrix of echo are established. Based on the analysis of the characteristics of covariance matrix, this paper generalizes the subspace and Capon method of sinusoidal signal spectrum estimation, and proposes three parameterized spectral moment estimation methods for low signal-to-noise ratio (SNR). The estimated value is obtained by a two-dimensional search on the spectral width and the average frequency. In this paper, the cost function is constructed based on the least square fitting idea, and a spectral moment estimation method based on the fitting of spectrum and autocorrelation function is proposed for the estimation of spectral moments when multiple Gao Si spectra are mixed. The problem of estimation of spectral moments when multiple Gao Si spectral echoes are mixed is solved by cyclic optimization. Finally, the performance of the method is verified by Monte Carlo simulation. In this paper, a fast calculation method of spectral moment estimation is proposed, which converts the two-dimensional search into two one-dimensional search, which can reduce the computation cost. Ground clutter is the most important factor affecting airborne meteorological radar detection. In this paper, the characteristics of meteorological target echo and ground clutter in frequency domain are analyzed, and a method of ground clutter suppression based on spectrum width is proposed. The performance of the algorithm is analyzed from the change of echo intensity and spectrum characteristic after suppression, and it is proved that the proposed method can suppress ground clutter effectively.
【学位授予单位】：天津大学
【学位级别】：博士
【学位授予年份】：2014
【分类号】：TN957.51
[Abstract]:Airborne weather radar is a compulsory installation of airborne electronic equipment on civil aviation aircraft, equivalent to the "eyes" of the aircraft, which can detect the rainstorm, turbulence and windshear areas in the flight path in real time. Provide pilots with weather warning and safe flight paths. The detection of meteorological targets by airborne meteorological radar is realized through a series of complex signal and data processing processes. Signal processing unit is an important component to determine the performance of airborne meteorological radar system. Some key technologies of airborne meteorological radar signal processing are studied in this paper. The main work is summarized as follows. 1. In this paper, two common simulation methods are compared, one is based on echo statistics and the other is based on the microphysical characteristics of meteorological target. A simulation scheme of airborne meteorological radar echo in the whole flight phase combining with airborne fast access recorder data is proposed. 2. Airborne weather radar detects rain area turbulence and wind shear by Doppler processing of echo namely estimating three spectral moments of echo: power average Doppler frequency and spectrum width. The non-parameterized pulse pair method is widely used in meteorological radar systems, but it is not suitable for the cases of low signal-to-noise ratio (SNR) and multi-Gao Si spectrum superposition. In this paper, a parameterized estimation model is constructed to solve this problem by making full use of the characteristic of meteorological radar echo from Gao Si spectrum. Firstly, the mathematical models of spectrum, autocorrelation function and covariance matrix of echo are established. Based on the analysis of the characteristics of covariance matrix, this paper generalizes the subspace and Capon method of sinusoidal signal spectrum estimation, and proposes three parameterized spectral moment estimation methods for low signal-to-noise ratio (SNR). The estimated value is obtained by a two-dimensional search on the spectral width and the average frequency. In this paper, the cost function is constructed based on the least square fitting idea, and a spectral moment estimation method based on the fitting of spectrum and autocorrelation function is proposed for the estimation of spectral moments when multiple Gao Si spectra are mixed. The problem of estimation of spectral moments when multiple Gao Si spectral echoes are mixed is solved by cyclic optimization. Finally, the performance of the method is verified by Monte Carlo simulation. In this paper, a fast calculation method of spectral moment estimation is proposed, which converts the two-dimensional search into two one-dimensional search, which can reduce the computation cost. Ground clutter is the most important factor affecting airborne meteorological radar detection. In this paper, the characteristics of meteorological target echo and ground clutter in frequency domain are analyzed, and a method of ground clutter suppression based on spectrum width is proposed. The performance of the algorithm is analyzed from the change of echo intensity and spectrum characteristic after suppression, and it is proved that the proposed method can suppress ground clutter effectively.
【学位授予单位】：天津大学
【学位级别】：博士
【学位授予年份】：2014
【分类号】：TN957.51
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