تقرير
Unified Linearization-based Nonlinear Filtering
| العنوان: | Unified Linearization-based Nonlinear Filtering |
|---|---|
| المؤلفون: | Kullberg, Anton, Skog, Isaac, Hendeby, Gustaf |
| سنة النشر: | 2023 |
| مصطلحات موضوعية: | Electrical Engineering and Systems Science - Signal Processing |
| الوصف: | This letter shows that the following three classes of recursive state estimation filters: standard filters, such as the extended Kalman filter; iterated filters, such as the iterated unscented Kalman filter; and dynamically iterated filters, such as the dynamically iterated posterior linearization filters; can be unified in terms of a general algorithm. The general algorithm highlights the strong similarities between specific filtering algorithms in the three filter classes and facilitates an in-depth understanding of the pros and cons of the different filter classes and algorithms. We end with a numerical example showing the estimation accuracy differences between the three classes of filters when applied to a nonlinear localization problem. Comment: 4 pages, 1 page reference. arXiv admin note: text overlap with arXiv:2302.13871 |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2309.07631 |
| رقم الأكسشن: | edsarx.2309.07631 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |