多源融合导航系统的融合算法综述

唐璐杨; 唐小妹; 李柏渝; 刘小汇

doi:10.13442/j.gnss.1008-9268.2018.03.007

多源融合导航系统的融合算法综述

doi: 10.13442/j.gnss.1008-9268.2018.03.007

国防科技大学,电子科学学院,湖南长沙 410073

详细信息

作者简介:
唐璐杨(1994-),女,硕士研究生,主要从事多源融合导航算法研究。

通讯作者:
唐璐杨 E-mail: evatly@foxmail.com

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- 被引次数: 0
出版历程
- 刊出日期: 2018-09-05

A Survey of Fusion Algorithms for Multi-source Navigation Fusion System

College of Electronic Science, National University of Defense Technology, Changsha 410073, China

摘要

摘要: 多导航源的信息融合算法是多源融合导航系统的核心技术,根据各类算法的结构特性,将融合算法分为三大类:集中式融合算法、并行式融合算法和序贯式融合算法。通过对各类算法的仿真,总结出算法的特点和适用场景,并得出融合算法的发展趋势,为多源融合导航系统设计提供算法理论支撑。
- 多源融合导航系统 /
- 融合算法 /
- 组合导航
Abstract: Multi-source navigation information fusion algorithm is the core technology of multi-source fusion navigation system. According to the structure characteristics of various algorithms, fusion algorithms are divided into three categories: centralized fusion algorithm, parallel fusion algorithm and sequential fusion algorithm. Through the simulation of various algorithms, the characteristics and application scenarios of the algorithm are summarized, and the development trend of the fusion algorithm is obtained, which provides theoretical support for the design of multi-source fusion navigation system.
- Multi-source navigation fusion system /
- fusion algorithm /
- integrated navigation

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参考文献(15)

[1]	付晨. 多传感器融合导航的关键技术研究［D］. 成都：电子科技大学, 2014.
[2]	WILLNER D, CHANG C B, DUNN K P. Kalman filter configurations for multiple radar systems［S］. Nasa Sti／recon Technical Report N, 1976.
[3]	JIANG W C. Implementation of odometry with EKF in Hector SLAM methods［J］. International Journal of Automation ＆ Smart Technology, 2018,8(1):9-18.
[4]	HAMZAH N H, YAACOB S, JUNOH A K, et al. The study of particle filter for satellite angular rate estimation without rate sensor measurement［C］／／MATEC Web of Conference, 2018.
[5]	杨春,郭健,张磊,等. 采用卡方检验的模糊自适应无迹卡尔曼滤波组合导航算法［J］. 控制与决策, 2018(1):81-87.
[6]	朱军,李香君,付融冰,等. 双重遗忘卡尔曼滤波PMLSM无位置传感控制研究［J］. 系统仿真学报, 2018(2):672-678.
[7]	张玉龙,王茁,杨巍. 基于极大似然估计的新息自适应滤波算法［J］. 传感器与微系统, 2018(1):141-144.
[8]	ZHAO F, ZHAO G, FAN S, et al. Multiple model adaptive estimation algorithm for SINS／CNS integrated navigation system［C］／／Control Conference. IEEE, 2015:5286-5291.
[9]	PITTS W. How we know universals the perception of auditory and visual forms［J］. Bulletin of Mathematical Biophysics, 1947, 9(3):127.
[10]	SPEYER J. Computation and transmission requirements for a decentralized linear-quadratic-Gaussian control problem［J］. IEEE Transactions on Automatic Control, 1979, 24(2):266- 269.
[11]	CARLSON N A. Federated square root filter for decentralized parallel processors［J］. Aerospace ＆ Electronic Systems IEEE Transactions on, 1990, 26(3):517-525.
[12]	杨元喜. 多传感器融合导航方法的比较［J］. 测绘科学与工程, 2006(2):1-3.
[13]	杨元喜. 多源传感器动、静态滤波融合导航［J］. 武汉大学学报(信息科学版), 2003, 28(4):386-388.
[14]	KAESS M, DELLAERT F. Magnetic resonance imaging of hepatocellular carcinoma using contrast media.［J］. Oncology, 1991, 75(Suppl.1):65-71.
[15]	GROVES P D. GNSS与惯性及多传感器组合导航系统原理［M］. 北京:国防工业出版社, 2015.