摘要
针对机载气象雷达在复杂的地形环境下探测低空风切变时,地杂波呈现的非均匀特征导致难以准确获得杂波统计特性,进而影响杂波抑制效果,使得风切变风速估计不准的问题,该文提出一种色加载知识辅助STAP(CL-KA-STAP)的低空风切变风速估计方法。该方法首先构造降维联合时空变换矩阵,并对待检测距离单元的回波信号进行降维处理,然后将由数字高程模型(DEM)和国家土地覆盖数据库(NLCD)获取的先验知识融入到组合空时主通道自适应处理器(CMCAP)中,构造色加载系数优化函数求解色加载系数,最后构造滤波器,实现杂波自适应滤波并准确估计风速。后续仿真结果证明了所提方法的有效性。
When the airborne weather radar detects low-altitude wind shear in a complex terrain environment,the non-uniform characteristics of ground clutter make it difficult to accurately obtain clutter statistical characteristics,which in turn affects the clutter suppression effect,and makes the wind speed estimation of wind shear inaccurate.A Colored-Loading Knowledge-Aided STAP(CL-KA-STAP)wind speed estimation method of low-altitude wind shear is proposed.This method first constructs a dimensionality reduction joint space-time transformation matrix,and performs dimensionality reduction processing on the echo signal of the distance unit to be detected,and then integrates the prior knowledge obtained by the Digital Elevation Model(DEM)and the National Land Cover Database(NLCD)into the combined space.In the Combined space-time Main Channel Adaptive Processor(CMCAP),the color loading coefficient optimization function is constructed to solve the color loading coefficient,and finally the filter is constructed to realize the adaptive filtering of clutter and accurately estimate the wind speed.The subsequent simulation results prove the effectiveness of the proposed method.
作者
李海
谢伶莉
张志宁
LI Hai;XIE Lingli;ZHANG Zhining(Tianjin Key Lab for Advanced Signal Processing,Civil Aviation University of China,Tianjin 300300,China)
出处
《电子与信息学报》
EI
CSCD
北大核心
2021年第12期3647-3655,共9页
Journal of Electronics & Information Technology
基金
民机项目(MJ-2018-S-28)
天津市自然基金重点项目(20JCZDJC00490)
航空基金项目(20182067008)
中央高校基本科研业务费项目(3122018D008)
中国民航大学蓝天教学名师培养经费。
关键词
机载气象雷达
知识辅助
色加载
低空风切变
风速估计
Airborne weather radar
Knowledge Aided(KA)
Color loading
Low-altitude wind shear
Wind speed estimation