Institutional Repository of Coll Elect & Informat Engn
A novel parallel accelerated CRPF algorithm | |
Wang, Jinhua1,2,3; Cao, Jie1,2,3; Li, Wei1; Yu, Ping1,2,3; Huang, Kaijie1 | |
2019-10-17 | |
发表期刊 | APPLIED INTELLIGENCE |
ISSN | 0924-669X |
卷号 | 50期号:3页码:849-859 |
摘要 | Particle filtering is one of the most important algorithms for solving state estimation of nonlinear systems and has been widely studied in many fields. However, due to the unknown complex noise in the actual system, its estimation performance is degraded. Moreover, when the number of particles increase, the real-time performance of the algorithm is poor. For these two problems above, this paper proposed a parallel acceleration CRPF (cost-reference particle filter) algorithm based on CUDA (Compute Unified Device Architecture). CRPF does not need known noise statistics in nonlinear system state estimation, which can reduce the influence of unknown noise on state estimation accuracy. Combined with GPU's (Graphics Processing Unit) multi-thread parallel computing capability, CRPF parallel acceleration can be realized. Since the data association can't be parallel resampled, all the particles are evenly distributed to multiple blocks, and resampling process can be parallelized by block parallel computing, so as to improve the speed of the algorithm. At the same time, in order to reduce the global particle performance degradation caused by block resampling, the particles with low probability mass in each block are optimized by using a portion of global high-quality particles. Through two sets of simulation experiments, it is proved that the proposed method has improved in estimation accuracy and the real-time performance has been improved significantly, which can provide a new idea for the practical application of nonlinear filtering method. |
关键词 | Particle filter CRPF GPU Accelerated parallel processing CUDA |
DOI | 10.1007/s10489-019-01534-0 |
收录类别 | SCI ; SCIE ; EI |
语种 | 英语 |
资助项目 | National Natural Science Foundation of China[61763028] ; Natural science foundation of gansu province[1506RJZA105] |
WOS研究方向 | Computer Science |
WOS类目 | Computer Science, Artificial Intelligence |
WOS记录号 | WOS:000490854800001 |
出版者 | SPRINGER |
EI入藏号 | 20195107877162 |
EI主题词 | Graphics processing unit |
EI分类号 | 722.2 Computer Peripheral Equipment - 723.5 Computer Applications - 731.1 Control Systems - 922.2 Mathematical Statistics - 961 Systems Science |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | https://ir.lut.edu.cn/handle/2XXMBERH/31498 |
专题 | 电气工程与信息工程学院 |
通讯作者 | Wang, Jinhua |
作者单位 | 1.Lanzhou Univ Technol, Coll Elect & Informat Engn, Lanzhou 730050, Gansu, Peoples R China; 2.Lanzhou Univ Technol, Key Lab Gansu Adv Control Ind Proc, Lanzhou 730050, Gansu, Peoples R China; 3.Lanzhou Univ Technol, Natl Expt Teaching Ctr Elect & Control Engn, Lanzhou 730050, Gansu, Peoples R China |
第一作者单位 | 电气工程与信息工程学院; 兰州理工大学 |
通讯作者单位 | 电气工程与信息工程学院; 兰州理工大学 |
第一作者的第一单位 | 电气工程与信息工程学院 |
推荐引用方式 GB/T 7714 | Wang, Jinhua,Cao, Jie,Li, Wei,et al. A novel parallel accelerated CRPF algorithm[J]. APPLIED INTELLIGENCE,2019,50(3):849-859. |
APA | Wang, Jinhua,Cao, Jie,Li, Wei,Yu, Ping,&Huang, Kaijie.(2019).A novel parallel accelerated CRPF algorithm.APPLIED INTELLIGENCE,50(3),849-859. |
MLA | Wang, Jinhua,et al."A novel parallel accelerated CRPF algorithm".APPLIED INTELLIGENCE 50.3(2019):849-859. |
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Wang-A novel paralle(6030KB) | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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