Details

Autor(en) / Beteiligte

• Vo, Ba-Ngu
• Vo, Ba-Tuong
• Hoang, Hung Gia

Titel

An Efficient Implementation of the Generalized Labeled Multi-Bernoulli Filter

Ist Teil von

• IEEE transactions on signal processing, 2017-04, Vol.65 (8), p.1975-1987

Ort / Verlag

IEEE

Erscheinungsjahr

2017

Quelle

IEEE Electronic Library Online

Beschreibungen/Notizen

• This paper proposes an efficient implementation of the generalized labeled multi-Bernoulli (GLMB) filter by combining the prediction and update into a single step. In contrast to an earlier implementation that involves separate truncations in the prediction and update steps, the proposed implementation requires only one truncation procedure for each iteration. Furthermore, we propose an efficient algorithm for truncating the GLMB filtering density based on Gibbs sampling. The resulting implementation has a linear complexity in the number of measurements and quadratic in the number of hypothesized objects.