Deterministic Optimal Transport-based Gaussian Mixture Particle Filtering for Verifiable Applications
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arXiv
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866916587723816960 |
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| author | Popov, Andrey A Zanetti, Renato |
| author_facet | Popov, Andrey A Zanetti, Renato |
| contents | Mixture-model particle filters such as the ensemble Gaussian mixture filter require a resampling procedure in order to converge to exact Bayesian inference. Canonically, stochastic resampling is performed, which provides useful samples with no guarantee of usefulness for a finite ensemble. We propose a new resampling procedure based on optimal transport that deterministically selects optimal resampling points. We show on a toy 3-variable problem that it significantly reduces the amount of particles required for useful state estimation. Finally, we show that this filter improves the state estimation of a seldomly-observed space object in an NRHO around the moon. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2501_17302 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Deterministic Optimal Transport-based Gaussian Mixture Particle Filtering for Verifiable Applications Popov, Andrey A Zanetti, Renato Computation Optimization and Control Mixture-model particle filters such as the ensemble Gaussian mixture filter require a resampling procedure in order to converge to exact Bayesian inference. Canonically, stochastic resampling is performed, which provides useful samples with no guarantee of usefulness for a finite ensemble. We propose a new resampling procedure based on optimal transport that deterministically selects optimal resampling points. We show on a toy 3-variable problem that it significantly reduces the amount of particles required for useful state estimation. Finally, we show that this filter improves the state estimation of a seldomly-observed space object in an NRHO around the moon. |
| title | Deterministic Optimal Transport-based Gaussian Mixture Particle Filtering for Verifiable Applications |
| topic | Computation Optimization and Control |
| url | https://arxiv.org/abs/2501.17302 |