A PHD filter for tracking multiple AUVs

Author

Melo, Jose ; Matos, Anibal

Author_Institution

INESC TEC (formerly INESC Porto), Univ. of Porto, Porto, Portugal

fYear

2014

fDate

14-19 Sept. 2014

Firstpage

1

Lastpage

8

Abstract

In this paper we address the problem of tracking multiple AUVs using acoustic signals. Using For this challenging scenario, we propose to use a Probability Hypothesis Density Filter and present a suitable implementation of the Sequential Monte Carlo PHD filter. It will be demonstrated that a particle filter implementation of the aforementioned filter can be used to successfully track multiple AUVs, changing in number over time, using range measurements from the vehicles to a set of acoustic beacons. Simulation results will be presented that allow to evaluate the performance of the filter.

Keywords

Monte Carlo methods; acoustic applications; acoustic signal processing; autonomous underwater vehicles; marine navigation; multi-robot systems; particle filtering (numerical methods); probability; target tracking; acoustic beacons; acoustic signals; autonomous underwater vehicles; multiple AUV tracking; probability hypothesis density filter; range measurements; sequential Monte Carlo PHD filter; Acoustics; Approximation methods; Equations; Mathematical model; Navigation; Target tracking; Vehicles;

fLanguage

English

Publisher

ieee

Conference_Titel

Oceans - St. John's, 2014

Conference_Location

St. John´s, NL

Print_ISBN

978-1-4799-4920-5

Type

conf

DOI

10.1109/OCEANS.2014.7003170

Filename

7003170