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。
The clear air turbulence and the dry windshear cannot be effectively detected by the airborne weather radar because of the low signalto-noise ratio （SNR）. A parametric spectral moment estimation method is proposed, which is based on a nonlinear least-squares （NLS） fit of the autocorrelation sequence of the radar echoes. And the relaxation-based method is used to solve the NLS problem when the echoes are mixed up with several echoes with Gaussian-shaped spectrum. Also, a fast algorithm is given, which substitutes the 2D-search with a two 1D-search. Finally, theoretical and numerical simulation results are presented to verify the perform- ances. It is demonstrated that the presented method is effective in low SNR.
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2014年第3期447-452,共6页
Systems Engineering and Electronics
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
关键词
机载气象雷达
参数化谱矩估计
低信噪比
非线性最小二乘
循环优化
airborne weather radar
parametric spectral moments estimationl low signal-to-noise ratio
nonlinear least-squares （NLS）
cyclical optimization
