Robust fixed-lag smoothing under model perturbations

Shenglun Yi; Mattia Zorzi

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arXiv · 2210.16802

Robust fixed-lag smoothing under model perturbations

Shenglun Yi·Mattia Zorzi

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Abstract

A robust fixed-lag smoothing approach is proposed in the case there is a mismatch between the nominal model and the actual model. The resulting robust smoother is characterized by a dynamic game between two players: one player selects the least favorable model in a prescribed ambiguity set, while the other player selects the fixed-lag smoother minimizing the smoothing error with respect to least favorable model. We propose an efficient implementation of the proposed smoother. Moreover, we characterize the corresponding least favorable model over a finite time horizon. Finally, we test the robust fixed-lag smoother in two examples. The first one regards a target tracking problem, while the second one regards a parameter estimation problem.

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BibTeX RIS

Shenglun Yi, Mattia Zorzi. 2022-10-30. Robust fixed-lag smoothing under model perturbations. https://arxiv.org/abs/2210.16802

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