Study on group target tracking  to counter swarms of drones

Louis Guerlin; Benjamin Pannetier; Michèle Rombaut; Maxime Derome

doi:10.1117/12.2558119

22 April 2020 Study on group target tracking to counter swarms of drones

Louis Guerlin, Benjamin Pannetier, Michèle Rombaut, Maxime Derome

Proceedings Volume 11423, Signal Processing, Sensor/Information Fusion, and Target Recognition XXIX; 1142304 (2020) https://doi.org/10.1117/12.2558119
Event: SPIE Defense + Commercial Sensing, 2020, Online Only

Abstract

This article focuses on Group Target Tracking (GTT) to counter swarms of drones using Random Finite Sets (RFSs) and Random Matrix (RM) approaches. Tracking swarms of drones is analog to tracking extended targets that are characterized by their continuously evolving shape and composition. Extended target tracking for groups of targets finds various applications in the literature because detecting and tracking each individual target of a group is computationally demanding and unnecessary if the group itself can be modeled. Elliptic shapes offers a suitable representation for most groups, and their inference is quite inexpensive with the random matrix approach. Indeed, they are efficient when coupled with random finite sets based filters, which represents the current state of the art for Bayesian multi-target tracking. In this work, a practical implementation of a labeled Poisson/Multi-Bernoulli filter using random matrices for group target tracking is proposed. This study compares several random matrix prediction and update algorithms with and without random finite sets based filters on several dataset.

Conference Presentation

Citation Download Citation

Louis Guerlin, Benjamin Pannetier, Michèle Rombaut, and Maxime Derome "Study on group target tracking to counter swarms of drones", Proc. SPIE 11423, Signal Processing, Sensor/Information Fusion, and Target Recognition XXIX, 1142304 (22 April 2020); https://doi.org/10.1117/12.2558119

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