Reduced Sampling-Rate Rauch-Tung-Striebel Smoother
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en
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6
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Proceedings of the 2025 28th International Conference on Information Fusion, FUSION 2025
Abstract
The Rauch-Tung-Striebel (RTS) smoother is an algorithm for computing state estimates in time series using noisy measurements from all time steps. The RTS smoother works by first filtering the state when measurements arrive and then using a backward pass to obtain the smoothed state estimates for all time steps that use measurement information from all time steps as well. The backward pass goes through all time steps for which a filtering estimate were obtained in backward order. We propose a smoother that does the backward pass using only a fraction of the time steps and provides the same results as the conventional RTS smoother for these time steps. This reduces computational complexity and required memory significantly as only data for these interesting time steps need to be stored. We also propose the extension of the reduced sampling-rate smoother for non-linear systems. We show an example application involving position estimation using a state space model that uses a high filtering rate, but where it is suitable to present the final smoothed route with a considerably lower rate. In a second example, we show how the reduced rate smoother works in a nonlinear case.Description
Publisher Copyright: © 2025 ISIF.
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Raitoharju, M, García-Fernandez, Á F & Sarkka, S 2025, Reduced Sampling-Rate Rauch-Tung-Striebel Smoother. in Proceedings of the 2025 28th International Conference on Information Fusion, FUSION 2025. Proceedings of the 2025 28th International Conference on Information Fusion, FUSION 2025, IEEE, International Conference on Information Fusion, Rio de Janiero, Brazil, 07/07/2025. https://doi.org/10.23919/FUSION65864.2025.11124055