摘要
在局部平稳的杂波环境下,滑窗样本选取方法可以比较准确地估计检测单元的杂波统计特性。该文提出基于滑窗选取样本的递推QR算法,它采用双曲Householder变换实现QR分解的递推,能有效地抑制局部平稳杂波,且具有数值稳定性好,计算量小的优点。仿真数据处理和实测数据处理验证了该方法的有效性。
Secondary data acquired with sliding window method can accurately estimate clutter statistics of target-gate under localized stationary environment. In this paper, a recursive QR factorization method based on sliding window is presented, which adopts hyperbolic Househoulder transformation to realize the recursion of QR factorization. The method can not only suppress localized stationary clutter effectively, but also exhibit good numerical stability and low complexity. Simulation data processing results and real data processing results are given to demonstrate
出处
《电子与信息学报》
EI
CSCD
北大核心
2008年第10期2338-2342,共5页
Journal of Electronics & Information Technology
基金
雷达信号处理国家重点实验室基金(9140C010403060C01)资助课题
关键词
空时自适应处理
局部平稳杂波
QR分解
滑窗法
Space Time window method the effectiveness of the method Adaptive Processing（STAP）
Localized stationary clutter
QR factorization
Sliding
