Journal
IEEE ACCESS
Volume 7, Issue -, Pages 98820-98831Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2019.2929302
Keywords
Adaptive cubature kalman filtering (ACKF); consensus method; distributed estimation; stochastic boundedness
Categories
Funding
- National Natural Science Foundation of China [61873011, 61803014, 61503009, 61333011]
- Beijing Natural Science Foundation [4182035]
- Young Elite Scientists Sponsorship Program by the CAST [2017QNRC001]
- Aeronautical Science Foundation of China [2016ZA51005, 20170151001]
- Special Research Project of Chinese Civil Aircraft
- State Key Laboratory of Intelligent Control and Decision of Complex Systems
- Fundamental Research Funds for the Central Universities [YWF-18-BJ-Y-73]
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The distributed cubature Kalman filter is widely used in the field of target tracking, however, the presence of model uncertainties will undermine its tracking stability and effectiveness for tracking maneuvering target. In order to eliminate this effect on maneuvering target tracking, this paper develops a distributed consensus based strong tracking cubature Kalman filter scheme. First, each node obtains its local estimation with the usage of local observations via strong tracking cubature Kalman filter, where the suboptimal fading factor and adaptive factor are introduced for adaptively modifying the filter gain. Then, the designed filter gain is used for updating the local state estimation. Second, after all, nodes have achieved its local estimation, each node exchanges its local estimation to its neighbors and updates its local estimation according to the consensus communication protocol. It can be further proved that the distributed interaction between neighbors will contribute to enhancing the tracking stability. The detailed proof for stochastic boundedness of the estimation error is analyzed by introducing a stochastic process. Simulation results demonstrate that the proposed algorithm can achieve higher tracking accuracy than the existing methods for tracking a maneuvering target.
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