Decentralized Poisson Multi-Bernoulli Filtering for Vehicle Tracking
Journal article, 2020

A decentralized Poisson multi-Bernoulli filter is proposed to track multiple vehicles using multiple high-resolution sensors. Independent filters estimate the vehicles' presence, state, and shape using a Gaussian process extent model; a decentralized filter is realized through fusion of the filters posterior densities. An efficient implementation is achieved by parametric state representation, utilization of single hypothesis tracks, and fusion of vehicle information based on a fusion mapping. Numerical results demonstrate the performance.

Gaussian processes

target extent

posterior fusion

multitarget tracking

Author

Markus Fröhle

Zenuity AB

Karl Granström

Embark Trucks Inc.

Chalmers, Electrical Engineering, Signal Processing and Biomedical Engineering, Signal Processing

Henk Wymeersch

Chalmers, Electrical Engineering, Communication and Antenna Systems, Communication Systems

IEEE Access

2169-3536 (ISSN)

Vol. 8 126414-126427 9136678

COPPLAR CampusShuttle cooperative perception & planning platform

VINNOVA, 2016-01-01 -- 2018-12-31.

Subject Categories

Vehicle Engineering

Signal Processing

Computer Vision and Robotics (Autonomous Systems)

DOI

10.1109/ACCESS.2020.3008007

More information

Latest update

8/28/2020