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联邦滤波的改进算法
引用本文:高为广,孙岩峰,卢伟,顾青涛. 联邦滤波的改进算法[J]. 测绘科学技术学报, 2006, 23(4): 250-253
作者姓名:高为广  孙岩峰  卢伟  顾青涛
作者单位:1. 信息工程大学,测绘学院,河南,郑州,450052;61081部队,北京,100094
2. 61081部队,北京,100094
摘    要:分析并综述了联邦滤波算法,以及该算法存在的问题.针对观测信息不足的情况下,结合抗差估计和自适应估计理论对联邦滤波算法进行了改进,给出了联邦滤波在局部传感器观测信息不足情况下的改进算法.由模拟计算结果可知,在局部传感器观测信息不足的情况下,改进的联邦滤波器能较好地抑制载体观测异常和状态扰动异常对动态系统参数估值的影响,具有很强的的抗差性和自适应性.

关 键 词:预报残差  自适应抗差Kalman滤波  联邦滤波
文章编号:1673-6338(2006)04-0250-04
收稿时间:2006-03-21
修稿时间:2006-06-11

The Improved Algrithms of Federated Filtering
GAO Wei-guang,SUN Yan-feng,LU Wei,GU Qing-tao. The Improved Algrithms of Federated Filtering[J]. Journal of Zhengzhou Institute of Surveying and Mapping, 2006, 23(4): 250-253
Authors:GAO Wei-guang  SUN Yan-feng  LU Wei  GU Qing-tao
Affiliation:1 .Institute of Surveying and Mapping, Information Engineering University, Zhengzhou 450052, China; 2. 61081 Troops, Beijing 100094, China
Abstract:After a brief review of federated filtering, the shortcomings of federated filtering were analyzed and summarized. When the measurements were not enough, a new algorithm was set up based on the robust and adaptive estimation. It was shown, by derivations and calculations, that the new adaptive robust federated filtering could effectively control the measurement outliers and kinematic state disturbing.
Keywords:predicted residuals    adaptive robust    Kalman filtering   federated filtering
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