GOSPA-Driven multi-Bernoulli Gaussian Sensor Management

Jones, George and Garcia-Fernandez, Angel F ORCID: 0000-0002-6471-8455 (2024) GOSPA-Driven multi-Bernoulli Gaussian Sensor Management In: 2024 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI), 2024-9-4 - 2024-9-6.

Text GOSPA_Driven_multi_Bernoulli_Gaussian_Sensor_Management___MFI_2024 (10).pdf - Author Accepted Manuscript Available under License Creative Commons Attribution. Download (298kB) | Preview

Abstract

This paper presents a myopic sensor management algorithm for multiple target tracking with an agile single sensor that has a limited field of view (FOV), utilising a multi-Bernoulli filter. The sensor management algorithm aims to minimise the predicted mean square generalised optimal sub-pattern assignment (GOSPA) error. The aim is therefore to minimise the localisation error for detected targets, and the number of missed and false targets at the next time step. We present a tractable algorithm based on an upper bound of the mean square GOSPA error when single-target densities are Gaussian.

Item Type:	Conference Item (Unspecified)
Uncontrolled Keywords:	46 Information and Computing Sciences, 40 Engineering, 4001 Aerospace Engineering
Divisions:	Faculty of Science & Engineering Faculty of Science & Engineering > School of Electrical Engineering, Electronics and Computer Science
Depositing User:	Symplectic Admin
Date Deposited:	11 Feb 2025 08:23
Last Modified:	23 May 2026 09:24
DOI:	10.1109/MFI62651.2024.10705781
Related Websites:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3190229
Disclaimer:	The University of Liverpool is not responsible for content contained on other websites from links within repository metadata. Please contact us if you notice anything that appears incorrect or inappropriate.