Specifications

Title: Tracking and identification for GPS/DR integrated navigation system with unknown
parameters
Authors: Li, Jiang1 ; Qian, Fu-Cai1, 2 ; Liu, Ding1 ; Hu, Shao-Lin1/李江;钱富才;刘丁;胡绍林
Author affiliation: 1 School of Automation and Information Engineering, Xi'an University of
Technology, Xi'an 710048, China
2 State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an
710054, China
Corresponding author: Li, J. ([e-mail])
Source title: Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology
Abbreviated source title: Dianzi Yu Xinxi Xuebao
Volume: 35
Issue: 4
Issue date: April 2013
Publication year: 2013
Pages: 921-926
Language: Chinese
ISSN: 10095896
CODEN: DKXUEC
Document type: Journal article (JA)
Publisher: Science Press, 18,Shuangqing Street,Haidian, Beijing, 100085, China
Abstract: This paper propses a filtering method for GPS/DR (Global Positioning
System/Dead-Reckoning) integrated navigation system with unknown parameters. This method
firstly structures a self-organizing state space model, and then estimates the state vector by using
Monte Carlo filtering method for this new system model. Because particle filter is easy to make a
search of the unknown parameters into a subset of the initial sampling for the self-organization
model an artificial fish swarm-partical filter algorithm is put forward. The algorithm not only can
estimate the system state, but also can make the sampling distribution of the unknown
parameters move to the true parameter distribution. Ultimately, the true value of the unknown
parameters are identified. The simuliation results show the effectiveness of the proposed
method.
Number of references: 15
Main heading: Monte Carlo methods
Controlled terms: Algorithms - Identification (control systems) - Navigation systems -
State space methods
Uncontrolled terms: Artificial fish swarm algorithms - GPS/DR integrated navigations -
Integrated navigation systems - MONTE CARLO - Monte Carlo filtering - Parameter
distributions - Sampling distribution - Self-organizing state space models
Classification code: 434.4 Waterway Navigation - 723 Computer Software, Data Handling
and Applications - 731.1 Control Systems - 921 Mathematics - 922.2 Mathematical
Statistics
DOI: 10.3724/SP.J.1146.2012.01065
Database: Compendex
Compilation and indexing terms, © 2013 Elsevier Inc.