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- W3115285440 abstract "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." @default.
- W3115285440 created "2021-01-05" @default.
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- W3115285440 date "2021-01-01" @default.
- W3115285440 modified "2023-10-17" @default.
- W3115285440 title "Adaptive δ-Generalized Labeled Multi-Bernoulli Filter for Multi-Object Detection and Tracking" @default.
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- W3115285440 doi "https://doi.org/10.1109/access.2020.3047802" @default.
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