摘要
本文以某雷达角跟踪精度研究为主要背景,提出了提高角跟踪精度的自适应鲁棒平滑方法。该结构主要由鲁棒模糊滤波器,基于二次新息的自校正器,自适应胡倍尔(Huber)函数以及自适应α—β平滑器组成。这种方法首次从系统观点出发,统筹考滤了最优性、鲁棒以及实时性三个主要性能指标和滤波、平滑器器结构。最后比较了各平滑算法的性能指标,并说明了本算法的有效性。
In this paper, a new adaptive robust smoother is presented to solve the problem of radar bearing tracking accuracy. This research is based on the study of bearing tracking accuracy of some type radar. The robust smoother consists of a robust fuzzy filter, the second innovation self-tuning estimater, adaptive Huber's function and adaptive α-βsmoother. From system viewpoint, not only three indexes, optimality, robustness and realtime, but also the structures of filter and smoother have been overally considered. At last, the comparison of simulation results of each smoother is also presented to show the effectiveness of the proposed algorithms.
出处
《宇航学报》
EI
CAS
CSCD
北大核心
1991年第3期63-67,共5页
Journal of Astronautics
关键词
模糊集
鲁棒平滑器
目标跟踪
雷达
Fuzzy set, Adaptive robust smoother, Target tracking,Hubers proposal.
