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• W4320038059 abstract "In many practical applications, the prior statistics of process and measurement noises are inaccurate, and the heavy-tailed distributed noises are prone to occur due to outliers. To achieve state estimation under this situation, a new outlier-robust Kalman filter with Gaussian multi-scale mixture model (GMSMM-ORKF) is proposed. First, a GMSMM is presented to model the posterior probability density functions. Then, the hierarchical prior models on the mixture probability vectors and scale parameters are built. Furthermore, employing variational Bayesian inference, a GMSMM-ORKF is derived. Finally, the superiority of the filter is illustrated by the simulation and real data." @default.
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• W4320038059 date "2023-01-01" @default.
• W4320038059 modified "2023-10-14" @default.
• W4320038059 title "A Novel Outlier-Robust Filter with Gaussian Multi-scale Mixture Model" @default.
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• W4320038059 doi "https://doi.org/10.1007/978-981-19-6613-2_588" @default.
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