An algorithm for large-scale multitarget tracking and parameter estimation - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue IEEE Transactions on Aerospace and Electronic Systems Année : 2021

An algorithm for large-scale multitarget tracking and parameter estimation

Résumé

Modern tracking problems require fast, scalable, and robust solutions for tracking multiple targets from noisy sensor data. In this article, an algorithm that has linear computational complexity with respect to the number of targets and measurements is presented. The method is based on the propagation of the first two factorial cumulants of a point process. The algorithm is demonstrated for tracking a million targets in cluttered environments in the fastest time yet for any such solution. A low-computational-complexity solution to the problem of joint multitarget tracking and parameter estimation is also presented. The multitarget filtering approach utilizes a single-cluster point process method for joint multiobject estimation and parameter estimation and is shown to be more computationally efficient and robust than previous implementations.
Fichier non déposé

Dates et versions

hal-03359417 , version 1 (30-09-2021)

Identifiants

Citer

Mark Campbell, Daniel Clark, Flavio de Melo. An algorithm for large-scale multitarget tracking and parameter estimation. IEEE Transactions on Aerospace and Electronic Systems, 2021, 57 (4), pp.2053-2066. ⟨10.1109/TAES.2021.3098155⟩. ⟨hal-03359417⟩
18 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More