Multi-sensor Data Fusion with Network Delays and Correlated Noises

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

Journal of System Simulation ›› 2019, Vol. 31 ›› Issue (12): 2617-2625.doi: 10.16182/j.issn1004731x.joss.19-FZ0354E

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Multi-sensor Data Fusion with Network Delays and Correlated Noises

Zhang Shankai¹, Zhu Cui¹, Su Zhong², Dai Juan²

1. School of Information and Communication Engineering, Beijing Information Science and Technology University, Beijing 100101, China;
2. Beijing Key Laboratory of High Dynamic Navigation Technology, Beijing Information Science and Technology University, Beijing 100101, China

Received:2019-05-30 Revised:2019-07-20 Published:2019-12-13
About author:Zhang Shankai(1995-), male, Beijing, Master student, research direction: Networked data fusion.
Supported by:
National Natural Science Foundation of China (61603047), Scientific Research Project of Beijing Municipal Educational Commission (KM201911232014)

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.

Key words: correlated noises, communication delays, orthogonal transformation, buffer, sequential fusion filter

CLC Number:

TP274+.2

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.

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Multi-sensor Data Fusion with Network Delays and Correlated Noises

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