Adaptive IMM Smoothing Algorithms for Jumping Markov System With Mismatched Measurement Noise Covariance Matrix

In this article, the adaptive online state smoothing problem is studied for a Markov jump system where the measurement noise covariance matrix (MNCM) is unknown. To address this problem, two adaptive interacting multiple model online smoothing algorithms are proposed to jointly estimate the target s...

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Veröffentlicht in:	IEEE transactions on aerospace and electronic systems 2024-08, Vol.60 (4), p.5467-5480
Hauptverfasser:	Xu, Hong, Pan, Qin, Xu, Heng, Quan, Yinghui
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptation models Adaptive interacting multiple model (IMM) smoothing augmented-state Bayes methods Covariance matrices Estimation fixed-lag smoothing (FLS) measurement noise covariance matrix (MNCM) Noise Smoothing methods State estimation variational Bayesian (VB)
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