Real-Time Implementation of Particle-PHD Filter Based on GPU

Author

Lin Gao ; Xu Tang ; Ping Wei

Author_Institution

Sch. of Electron. Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China

fYear

2014

fDate

19-21 Dec. 2014

Firstpage

1674

Lastpage

1678

Abstract

This paper addresses the computational problem of particle-Probability Hypothesis Density filter (P-PHDF) in multitarget tracking. A parallelization implementation scheme for P-PHDF on graphics processing unit (GPU) under the Compute Unified Device Architecture (CUDA) framework is proposed. Simulation results show that nearly 20× speedup was achieved on GPU compared to its CPU version.

Keywords

graphics processing units; parallel architectures; particle filtering (numerical methods); probability; CPU; CUDA framework; GPU; P-PHDF; compute unified device architecture; graphics processing unit; multitarget tracking; parallelization implementation scheme; particle-probability hypothesis density filter; Clutter; Computer architecture; Estimation; Filtering algorithms; Graphics processing units; Signal processing algorithms; Target tracking; Compute Unified Device Architecture (CUDA); graphics processing unit (GPU); multitarget tracking; parallel computing; probability hypothesis density filter (PHDF);

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Science and Engineering (CSE), 2014 IEEE 17th International Conference on

Conference_Location

Chengdu

Print_ISBN

978-1-4799-7980-6

Type

conf

DOI

10.1109/CSE.2014.308

Filename

7023819