A data-driven particle filter for terrain based navigation of sensor-limited autonomous underwater vehicles

• Type: Article in International Scientific Journal
• Date: 2019

Authors

Melo, J (Author) Other; Aníbal Castilho Coimbra de Matos (Author) FEUP

Journal

Title: Asian Journal of Control

Vol. 21

Pages: 1659-1670

ISSN: 1561-8625

Publisher: Wiley-Blackwell

Indexing

ISI Web of Knowledge - 0 Citations

Scopus - 1 Citation

Other information

Authenticus ID: P-00Q-HMK

DOI: 10.1002/asjc.2107

Abstract (EN): In this article a new Data-Driven formulation of the Particle Filter framework is proposed. The new formulation is able to learn an approximate proposal distribution from previous data. By doing so, the need to explicitly model all the disturbances that might affect the system is relaxed. Such characteristics are particularly suited for Terrain Based Navigation for sensor-limited AUVs, where typical scenarios often include non-negligible sources of noise affecting the system, which are unknown and hard to model. Numerical results are presented that demonstrate the superior accuracy, robustness and efficiency of the proposed Data-Driven approach.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 12