Abstract
Unlike the PHD and CPHD filters, which are respectively the first- and second-order moment approximations of the multi-target Bayesian recursion, the multi-Bernoulli (MB) filter is the probability density approximation of the complete multi-target Bayesian recursion.
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Notes
- 1.
Please note that the target spawning is not taken into consideration herein.
- 2.
The Frechet derivative is defined as \(\lim_{{\lambda \to 0^{ + } }} {{(G_{U,k} [h + \lambda \zeta ;{\varvec{z}}] - G_{U,k} [h;{\varvec{z}}])} \mathord{\left/ {\vphantom {{(G_{U,k} [h + \lambda \zeta ;{\varvec{z}}] - G_{U,k} [h;{\varvec{z}}])} \lambda }} \right. \kern-0pt} \lambda }\) [14].
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Wu, W., Sun, H., Zheng, M., Huang, W. (2023). Multi-Bernoulli Filter. In: Target Tracking with Random Finite Sets. Springer, Singapore. https://doi.org/10.1007/978-981-19-9815-7_6
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DOI: https://doi.org/10.1007/978-981-19-9815-7_6
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Publisher Name: Springer, Singapore
Print ISBN: 978-981-19-9814-0
Online ISBN: 978-981-19-9815-7
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