실시간 탄도 궤적 목표물 추적을 위한 GPU 기반 병렬적 Monte Carlo 최적화 기법Parallelized Monte Carlo Optimization With GPU for Real-time Ballistic Target Tracking
- Other Titles
- Parallelized Monte Carlo Optimization With GPU for Real-time Ballistic Target Tracking
- Authors
- 박주현; 이민준; 이헌철; 황예지; 최원석; 정보라
- Issue Date
- Aug-2023
- Publisher
- 제어·로봇·시스템학회
- Keywords
- ballistic target tracking; monte carlo optimization; GPU-based parallelization; .
- Citation
- 제어.로봇.시스템학회 논문지, v.29, no.8, pp 607 - 619
- Pages
- 13
- Journal Title
- 제어.로봇.시스템학회 논문지
- Volume
- 29
- Number
- 8
- Start Page
- 607
- End Page
- 619
- URI
- https://scholarworks.bwise.kr/kumoh/handle/2020.sw.kumoh/26421
- DOI
- 10.5302/J.ICROS.2023.23.0061
- ISSN
- 1976-5622
- Abstract
- This paper seeks to achieve real-time high-speed ballistic target tracking. Monte Carlo optimization can be considered to solve the non-linearity in motion and measurement models in high-speed targets, but applying it to real-time tracking systems is difficult because it requires a long computation time. This paper proposes a graphics processing unit (GPU)-based parallelization method to accelerate Monte Carlo optimization for real-time ballistic target tracking. The improved performance of the proposed method was tested and analyzed on awidelyused embedded system. Comparisons with existing Monte Carlo optimization on a central processing unit (CPU) revealed that the proposed method improved the real-time performance by greatly reducing the computation time.
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