Federated unscented particle filtering algorithm for SINS/CNS/GPS system |
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Authors: | Hai-dong Hu Xian-lin Huang Ming-ming Li and Zhuo-yue Song |
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Affiliation: | [1]Center for Control Theory and Guidance Technology, Harbin Institute of Technology, Harbin 150001, China [2]School of Electrical and Electronic Engineering, University of Manchester, Manchester M60 IQD, UK |
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Abstract: | To solve the problem of information fusion in the strapdown inertial navigation system (SINS)/celestial navigation system
(CNS)/global positioning system (GPS) integrated navigation system described by the nonlinear/non-Gaussian error models, a
new algorithm called the federated unscented particle filtering (FUPF) algorithm was introduced. In this algorithm, the unscented
particle filter (UPF) served as the local filter, the federated filter was used to fuse outputs of all local filters, and
the global filter result was obtained. Because the algorithm was not confined to the assumption of Gaussian noise, it was
of great significance to integrated navigation systems described by the non-Gaussian noise. The proposed algorithm was tested
in a vehicle’s maneuvering trajectory, which included six flight phases: climbing, level flight, left turning, level flight,
right turning and level flight. Simulation results are presented to demonstrate the improved performance of the FUPF over
conventional federated unscented Kalman filter (FUKF). For instance, the mean of position-error decreases from (0.640×10?6 rad, 0.667×10?6 rad, 4.25 m) of FUKF to (0.403×10?6 rad, 0.251×10?6 rad, 1.36 m) of FUPF. In comparison of the FUKF, the FUPF performs more accurate in the SINS/CNS/GPS system described by
the nonlinear/non-Gaussian error models. |
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Keywords: | navigation system integrated navigation unscented Kalman filter unscented particle filter |
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