A new multi-target tracking algorithm for a large number of orbiting objects - Université Toulouse III - Paul Sabatier - Toulouse INP Accéder directement au contenu
Article Dans Une Revue Advances in Space Research Année : 2019

A new multi-target tracking algorithm for a large number of orbiting objects

Résumé

This paper presents the filter for Hypothesised and Independent Stochastic Populations (HISP), a multi-object joint detection/tracking algorithm derived from a recent estimation framework for stochastic populations, in the context of Space Situational Awareness. Designed for multi-object estimation problems where the data association between tracks and collected observations is moderately ambiguous, the HISP filter has a linear complexity with the number of objects and the number of observations. Because of its scalable complexity, the HISP filter is a promising solution for the construction of a large-scale catalogue of Resident Space Objects. We illustrate the HISP filter on a challenging surveillance scenario built from real data for 115 satellites of PlanetLabs’ Dove constellation, and simulated observations collected from two sensors with limited coverage and measurement noise, in the presence of false positives and missed detection.
Fichier non déposé

Dates et versions

hal-02448332 , version 1 (22-01-2020)

Identifiants

Citer

Emmanuel Delande, Jeremie Houssineau, José Franco, Carolin Frueh, Daniel E Clark, et al.. A new multi-target tracking algorithm for a large number of orbiting objects. Advances in Space Research, 2019, 64 (3), pp.645-667. ⟨10.1016/j.asr.2019.04.012⟩. ⟨hal-02448332⟩
15 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More