Distributed particle filters via barycenters in 2-Wasserstein space
We develop a new version of distributed particle filters that exploits the novel theory of 2Wasserstein barycenters. We consider a wireless sensor network deployed over a vast geographical region where each sensor makes local observations and transmits a target state estimate to the Fusion center (FC...
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Final Year Project (FYP) |
| Language: | English |
| Published: |
Nanyang Technological University
2022
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/156814 |
| _version_ | 1811695312989847552 |
|---|---|
| author | Sheng, Shunan |
| author2 | Ariel Neufeld |
| author_facet | Ariel Neufeld Sheng, Shunan |
| author_sort | Sheng, Shunan |
| collection | NTU |
| description | We develop a new version of distributed particle filters that exploits the novel theory of 2Wasserstein barycenters. We consider a wireless sensor network deployed over a vast geographical region where each sensor makes local observations and transmits a target state estimate to the Fusion center (FC). Subsequently, the FC produces a global target state estimate based on the transmitted data. We propose the One-step Particle Filters (OPFs) and the Iterative Particle Filters (IPFs) to accommodate scenarios where the sensors communicate at the end stage or at each stage, respectively. Moreover, we present a comprehensive study of the convergence results of the One-step Particle Filters. Finally, we validate our algorithms using synthetic experiments and demonstrate the effectiveness of our proposed approaches. |
| first_indexed | 2024-10-01T07:21:29Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/156814 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T07:21:29Z |
| publishDate | 2022 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1568142023-02-28T23:17:25Z Distributed particle filters via barycenters in 2-Wasserstein space Sheng, Shunan Ariel Neufeld School of Physical and Mathematical Sciences Xiang, Qikun ariel.neufeld@ntu.edu.sg Science::Mathematics::Statistics We develop a new version of distributed particle filters that exploits the novel theory of 2Wasserstein barycenters. We consider a wireless sensor network deployed over a vast geographical region where each sensor makes local observations and transmits a target state estimate to the Fusion center (FC). Subsequently, the FC produces a global target state estimate based on the transmitted data. We propose the One-step Particle Filters (OPFs) and the Iterative Particle Filters (IPFs) to accommodate scenarios where the sensors communicate at the end stage or at each stage, respectively. Moreover, we present a comprehensive study of the convergence results of the One-step Particle Filters. Finally, we validate our algorithms using synthetic experiments and demonstrate the effectiveness of our proposed approaches. Bachelor of Science in Mathematical Sciences 2022-04-24T07:14:39Z 2022-04-24T07:14:39Z 2022 Final Year Project (FYP) Sheng, S. (2022). Distributed particle filters via barycenters in 2-Wasserstein space. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/156814 https://hdl.handle.net/10356/156814 en application/pdf Nanyang Technological University |
| spellingShingle | Science::Mathematics::Statistics Sheng, Shunan Distributed particle filters via barycenters in 2-Wasserstein space |
| title | Distributed particle filters via barycenters in 2-Wasserstein space |
| title_full | Distributed particle filters via barycenters in 2-Wasserstein space |
| title_fullStr | Distributed particle filters via barycenters in 2-Wasserstein space |
| title_full_unstemmed | Distributed particle filters via barycenters in 2-Wasserstein space |
| title_short | Distributed particle filters via barycenters in 2-Wasserstein space |
| title_sort | distributed particle filters via barycenters in 2 wasserstein space |
| topic | Science::Mathematics::Statistics |
| url | https://hdl.handle.net/10356/156814 |
| work_keys_str_mv | AT shengshunan distributedparticlefiltersviabarycentersin2wassersteinspace |