基于多传感器的序贯式融合有限域<i>H</i><sup>∞</sup>滤波方法

冯肖亮; 文成林; 刘伟峰; 李晓芳; 徐立中

doi:10.3724/SP.J.1004.2013.01523

基于多传感器的序贯式融合有限域H^∞滤波方法

doi: 10.3724/SP.J.1004.2013.01523

1.
河海大学计算机与信息学院南京 211100;
2.
河南工业大学电气工程学院郑州 450001;
3.
杭州电子科技大学自动化学院系统科学与控制工程研究所杭州 310018

基金项目:

国家自然科学基金(60934009, 61172133, 61175030, 91016020)资助

详细信息

作者简介:
冯肖亮河海大学计算机与信息学院博士研究生.主要研究方向为多源信息融合,目标跟踪,无线传感器网络.E-mail: fengxl2002@163.com

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出版历程
- 收稿日期: 2012-01-06
- 修回日期: 2012-08-06
- 刊出日期: 2013-09-20

Sequential Fusion Finite Horizon H^∞ Filtering for Multisenor System

1.
College of Computer and Information Engineering, Hohai University, Nanjing 211100;
2.
College of Electrical Engineering, Henan University of Technology, Zhengzhou 450001;
3.
Institute of Systems Science and Control Engineering, College of Automation, Hangzhou Dianzi University, Hangzhou 310018

Funds:

Supported by National Natural Science Foundation of China (60934009, 61172133, 61175030, 91016020)

摘要

摘要: 与集中式和分布式融合滤波器相比, 序贯式融合滤波器不仅保证了估计精度相同, 而且在对测量值即到达即滤波、部分测量值缺失等方面都具有灵活性、自适应性和实时性等特点. 为此, 本文针对一类噪声能量有界的多传感器动态系统, 给出了一种序贯式融合有限域H∞滤波器. 首先, 利用测量值扩维的方法, 给出一种集中式融合有限域H∞ 滤波器; 然后, 利用H∞滤波的性能指标与二次型不等式之间、以及Hilbert空间二次型的稳定点与Krein空间正交投影之间等的对应关系, 构造出一种序贯式融合有限域H∞ 滤波器; 最后, 从理论与数值仿真两方面验证了新滤波器与集中式融合有限域H∞滤波器的性能等价性.
- 融合估计 /
- 序贯式融合 /
- 有限域H∞滤波 /
- Krein空间
Abstract: Compared with the centralized fusion filter and the distributed one, sequential fusion filter not only works with the same fusion estimation precision, but also with the advantages of flexibility, adaptively, real-time and so on. Therefore, a novel sequential fusion H∞ filter is proposed for the multisensor system with bounded energy noises in this paper. Firstly, utilizing the method of measurement augmented, a centralized fusion finite horizon H∞ filter is given. Then, based on the correspond relationship between the H∞ filtering performance index and the quadratic inequality, and the relationship between the stationary point of the quadratic form in Hilbert space and the projection in Krein space, a novel sequential fusion finite horizon H∞ filter is derived in this paper. Finally, the equivalency of the new filter and the centralized fusion finite horizon H∞ filter is demonstrated from theory analysis and numerical simulation.
- Fusion estimation /
- sequential fusion /
- finite horizon H∞ filtering /
- Krein space

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参考文献(17)

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