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
Henk Wymeersch
Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks
IEEE Access
2169-3536 (ISSN) 21693536 (eISSN)
Vol. 8 126414-126427 9136678COPPLAR CampusShuttle cooperative perception & planning platform
VINNOVA (2015-04849), 2016-01-01 -- 2018-12-31.
Subject Categories
Vehicle Engineering
Signal Processing
Computer Vision and Robotics (Autonomous Systems)
DOI
10.1109/ACCESS.2020.3008007