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- Title
Hardware architecture and optimisation of FPP particle PHD filter for multi-target tracking in cyber-physical systems.
- Authors
Chao Li; Zhiguo Shi; Jiming Chen
- Abstract
To meet the rapidly growing demand of localisation and tracking information of mobile agents in cyber-physical systems, in this paper, we propose a fully pipelined and parallel (FPP) hardware architecture of particle probability hypothesis density (PHD) filter for multi-target tracking on the multi-cores processor hardware platforms, where an improved resampling algorithm is designed. We formulate the demand of minimising the processing delay in this architecture as an optimisation problem, which can be efficiently solved by transforming it to a group of mixed non-linear integer programming problems. Delay analysis shows that the proposed FPP particle PHD filter achieves significant improvement of real-time performance, and simulation results demonstrate that tracking performance remains at the same level as traditional particle PHD filters.
- Subjects
CYBER physical systems; COMPUTER input-output equipment; PROBABILITY theory; PIPELINED ADCs; INDUSTRIAL efficiency; REAL-time computing
- Publication
IET Control Theory & Applications (Wiley-Blackwell), 2017, Vol 11, Issue 11, p1830
- ISSN
1751-8644
- Publication type
Article
- DOI
10.1049/iet-cta.2016.1405