Multi-sensor Data Fusion with Network Delays and Correlated Noises

Authors

Shankai Zhang, 1. School of Information and Communication Engineering, Beijing Information Science and Technology University, Beijing 100101, China; ;
Zhu Cui, 1. School of Information and Communication Engineering, Beijing Information Science and Technology University, Beijing 100101, China; ;
Su Zhong, 2. Beijing Key Laboratory of High Dynamic Navigation Technology, Beijing Information Science and Technology University, Beijing 100101, China;
Dai Juan, 2. Beijing Key Laboratory of High Dynamic Navigation Technology, Beijing Information Science and Technology University, Beijing 100101, China;

Abstract

Abstract: This paper focuses on the state estimation for multi-sensor system with network delays and correlated noises. An orthogonal transformation method is applied to remove the correlations between different noises. For the problem of packet delays due to the unreliable network, a buffer with certain length is introduced to store the measurements, and the measurements are reordered using a timestamp in the buffer. Based on that, a novel sequential data fusion algorithm is proposed, by which the influence of the noise correlation and packet delays can be weakened effectively. Compared with the traditional sequential fusion method, the proposed algorithm has higher estimation accuracy. Simulation results show the effectiveness of the proposed algorithms.

Recommended Citation

Zhang, Shankai; Cui, Zhu; Zhong, Su; and Juan, Dai (2019) "Multi-sensor Data Fusion with Network Delays and Correlated Noises," Journal of System Simulation: Vol. 31: Iss. 12, Article 7.
DOI: 10.16182/j.issn1004731x.joss.19-FZ0354E
Available at: https://dc-china-simulation.researchcommons.org/journal/vol31/iss12/7

First Page

2617

Revised Date

2019-07-20

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.19-FZ0354E

Last Page

2625

CLC

TP274+.2

Recommended Citation

Zhang Shankai, Zhu Cui, Su Zhong, Dai Juan. Multi-sensor Data Fusion with Network Delays and Correlated Noises[J]. Journal of System Simulation, 2019, 31(12): 2617-2625.

DOI

10.16182/j.issn1004731x.joss.19-FZ0354E