基于非线性最小二乘的机载气象雷达回波谱矩估计方法
发布时间：2018-10-22 17:15
【摘要】：机载气象雷达无法检测雷达回波信噪比(signal-to-noise ratio,SNR)很低的晴空湍流和干性风切变。提出了一种参数化的机载气象雷达回波谱矩估计方法,该方法利用非线性最小二乘(nonlinear least-squares,NLS)方法拟合回波的自相关序列估计谱矩。引入循环优化思想来解决多个高斯谱回波混合时的谱矩估计问题。给出了将谱矩估计的二维搜索问题转化为两个一维搜索的快速算法。理论和仿真实验与分析表明,提出的方法适用于信噪比较低的情况。
[Abstract]:Airborne weather radar can not detect radar echo signal to noise ratio (signal-to-noise ratio,SNR) low clear air turbulence and dry wind shear. A parameterized method for estimating the echo spectral moments of airborne meteorological radar is proposed. The nonlinear least square (nonlinear least-squares,NLS) method is used to fit the autocorrelation sequence estimation of the spectral moments of the echo. The idea of cyclic optimization is introduced to solve the problem of estimation of spectral moments when several Gao Si spectral echoes are mixed. In this paper, a fast algorithm for converting the two-dimensional search problem of spectral moment estimation into two one-dimensional search algorithms is presented. Theoretical and simulation experiments and analysis show that the proposed method is suitable for the case of low signal-to-noise ratio (SNR).
【作者单位】： 天津大学电子信息工程学院;中国民航大学智能信号与图像处理天津市重点实验室;
【基金】：国家自然科学基金(61071194) 中央高校基金中国民航大学专项(ZXH2012D006)资助课题
【分类号】：TN959.4
[Abstract]:Airborne weather radar can not detect radar echo signal to noise ratio (signal-to-noise ratio,SNR) low clear air turbulence and dry wind shear. A parameterized method for estimating the echo spectral moments of airborne meteorological radar is proposed. The nonlinear least square (nonlinear least-squares,NLS) method is used to fit the autocorrelation sequence estimation of the spectral moments of the echo. The idea of cyclic optimization is introduced to solve the problem of estimation of spectral moments when several Gao Si spectral echoes are mixed. In this paper, a fast algorithm for converting the two-dimensional search problem of spectral moment estimation into two one-dimensional search algorithms is presented. Theoretical and simulation experiments and analysis show that the proposed method is suitable for the case of low signal-to-noise ratio (SNR).
【作者单位】： 天津大学电子信息工程学院;中国民航大学智能信号与图像处理天津市重点实验室;
【基金】：国家自然科学基金(61071194) 中央高校基金中国民航大学专项(ZXH2012D006)资助课题
【分类号】：TN959.4
【共引文献】
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