Earticle

초록

영어

In this paper, a multisensor distributed information fusion state estimator for discrete time stochastic linear systems with random sensor errors is presented. Based on state-space model, the white noise estimator and the observation predictor are applied in this algorithm. Modern time series analysis method and Gevers-Wouters(G-W) algorithm are also used in this paper. The algorithm can deal with the filtering, smoothing and prediction problems via a unified method. In order to improve the estimation accuracy, the multisensor distributed information fusion method is adopted, which calculates the weighting parameters with the forms of matrix, diagonal matrices and scalars respectively, in the sense of linear minimum variance. Among those three kinds of fusion methods, the method weighted by matrix has the highest accuracy but more computation, while the one weighted by scalar has the lowest accuracy but less computation. A simulation example for a typical tracking system with 3-sensor shows the correctness, validity and no obvious difference among three kinds of the fusion algorithms.

목차

Abstract
 1. Introduction
 2. Problem Formulation
 3. Local Optimal State Estimator
 4. Information Fusion Optimal State Estimator
 5. Simulation Example
 6. Conclusions
 Acknowledgment
 References

키워드

저자

• Yun Li [ School of Computer and Information Engineering, Harbin University of Commerce Heilongjiang, Harbin, 150001, China ]
• Gang Hao [ Electronic Engineering Institute, Heilongjiang University Heilongjiang, Harbin, 150080, China ] Corresponding Author
• Ming Zhao [ School of Computer and Information Engineering, Harbin University of Commerce Heilongjiang, Harbin, 150001, China ]
• Junling Li [ School of Computer and Information Engineering, Harbin University of Commerce Heilongjiang, Harbin, 150001, China ]
• Hao Jin [ School of Computer and Information Engineering, Harbin University of Commerce Heilongjiang, Harbin, 150001, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Hybrid Information Technology

• 간기

  격월간

• pISSN

  1738-9968

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605