| Autor: |
Zong-Xiang Liu, Jie Gan, Jin-Song Li, Mian Wu |
| Jazyk: |
angličtina |
| Rok vydání: |
2021 |
| Předmět: |
|
| Zdroj: |
IEEE Access, Vol 9, Pp 2100-2109 (2021) |
| Druh dokumentu: |
article |
| ISSN: |
2169-3536 |
| DOI: |
10.1109/ACCESS.2020.3047802 |
| Popis: |
The δ-generalized labeled multi-Bernoulli (δ-GLMB) filter is an efficient approach for multiobject tracking in case of high clutter density and low detection probability. However, the formulation of the original δ-GLMB filter requires that the birth δ-GLMB filtering density is known a priori. It is inapplicable for the birth object appearing from unknown positions. To address this problem, an adaptive δ-GLMB filter is proposed to detect and track the birth objects with unknown position information. This adaptive filter establishes the birth δ-GLMB filtering density by using measurements at previous three successive times. Simulation results indicate that the proposed adaptive δ-GLMB filter may efficiently detect and track the multiple objects with unknown positions. Simulation results also demonstrate that the proposed adaptive δ-GLMB filter performs better than the other existing adaptive filters. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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