التفاصيل البيبلوغرافية
| العنوان: |
Multisensor Fusion Estimation for Systems with Uncertain Measurements, Based on Reduced Dimension Hypercomplex Techniques |
| المؤلفون: |
Rosa M. Fernández-Alcalá, José D. Jiménez-López, Jesús Navarro-Moreno, Juan C. Ruiz-Molina |
| المصدر: |
Mathematics; Volume 10; Issue 14; Pages: 2495 |
| بيانات النشر: |
Multidisciplinary Digital Publishing Institute |
| سنة النشر: |
2022 |
| المجموعة: |
MDPI Open Access Publishing |
| مصطلحات موضوعية: |
hypercomplex algebra, missing measurements, multi-sensor information fusion estimation, random delayed measurements, ? k -proper signals |
| الوصف: |
The prediction and smoothing fusion problems in multisensor systems with mixed uncertainties and correlated noises are addressed in the tessarine domain, under Tk-properness conditions. Bernoulli distributed random tessarine processes are introduced to describe one-step randomly delayed and missing measurements. Centralized and distributed fusion methods are applied in a Tk-proper setting, k=1,2, which considerably reduce the dimension of the processes involved. As a consequence, efficient centralized and distributed fusion prediction and smoothing algorithms are devised with a lower computational cost than that derived from a real formalism. The performance of these algorithms is analyzed by using numerical simulations where different uncertainty situations are considered: updated/delayed and missing measurements. |
| نوع الوثيقة: |
text |
| وصف الملف: |
application/pdf |
| اللغة: |
English |
| العلاقة: |
Probability and Statistics; https://dx.doi.org/10.3390/math10142495Test |
| DOI: |
10.3390/math10142495 |
| الإتاحة: |
https://doi.org/10.3390/math10142495Test |
| حقوق: |
https://creativecommons.org/licenses/by/4.0Test/ |
| رقم الانضمام: |
edsbas.EBC0E88C |
| قاعدة البيانات: |
BASE |
