Optimal estimation of sensor biases for asynchronous multi-sensor data fusion
文献类型：期刊论文
| 作者 | Pu, Wenqiang1; Liu, Ya-Feng2 ; Yan, Junkun1; Liu, Hongwei1; Luo, Zhi-Quan3
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| 刊名 | MATHEMATICAL PROGRAMMING
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| 出版日期 | 2018-07-01 |
| 卷号 | 170期号:1页码:357-386 |
| 关键词 | Block coordinate decent algorithm Nonlinear least squares Sensor registration problem Tightness of semidefinite relaxation |
| ISSN号 | 0025-5610 |
| DOI | 10.1007/s10107-018-1304-2 |
| 英文摘要 | An important step in a multi-sensor surveillance system is to estimate sensor biases from their noisy asynchronous measurements. This estimation problem is computationally challenging due to the highly nonlinear transformation between the global and local coordinate systems as well as the measurement asynchrony from different sensors. In this paper, we propose a novel nonlinear least squares formulation for the problem by assuming the existence of a reference target moving with an (unknown) constant velocity. We also propose an efficient block coordinate decent (BCD) optimization algorithm, with a judicious initialization, to solve the problem. The proposed BCD algorithm alternately updates the range and azimuth bias estimates by solving linear least squares problems and semidefinite programs. In the absence of measurement noise, the proposed algorithm is guaranteed to find the global solution of the problem and the true biases. Simulation results show that the proposed algorithm significantly outperforms the existing approaches in terms of the root mean square error. |
| 资助项目 | National Natural Science Foundation of China (NSFC) Key Project Grant[61731018] ; NSFC[11331012] ; NSFC[11631013] ; NSFC[61601340] ; China National Funds for Distinguished Young Scientists Grant[61525105] |
| WOS研究方向 | Computer Science ; Operations Research & Management Science ; Mathematics |
| 语种 | 英语 |
| WOS记录号 | WOS:000435787200014 |
| 出版者 | SPRINGER HEIDELBERG |
| 源URL | [http://ir.amss.ac.cn/handle/2S8OKBNM/30613]  |
| 专题 | 计算数学与科学工程计算研究所 |
| 通讯作者 | Luo, Zhi-Quan |
| 作者单位 | 1.Xidian Univ, Natl Lab Radar Signal Proc, Collaborat Innovat Ctr Informat Sensing & Underst, Xian 710071, Shaanxi, Peoples R China 2.Chinese Acad Sci, State Key Lab Sci & Engn Comp, Inst Computat Math & Sci Engn Comp, Acad Math & Syst Sci, Beijing 100190, Peoples R China 3.Chinese Univ Hong Kong, Shenzhen Res Inst Big Data, Shenzhen 518172, Peoples R China |
| 推荐引用方式 GB/T 7714 | Pu, Wenqiang,Liu, Ya-Feng,Yan, Junkun,et al. Optimal estimation of sensor biases for asynchronous multi-sensor data fusion[J]. MATHEMATICAL PROGRAMMING,2018,170(1):357-386. |
| APA | Pu, Wenqiang,Liu, Ya-Feng,Yan, Junkun,Liu, Hongwei,&Luo, Zhi-Quan.(2018).Optimal estimation of sensor biases for asynchronous multi-sensor data fusion.MATHEMATICAL PROGRAMMING,170(1),357-386. |
| MLA | Pu, Wenqiang,et al."Optimal estimation of sensor biases for asynchronous multi-sensor data fusion".MATHEMATICAL PROGRAMMING 170.1(2018):357-386. |
入库方式： OAI收割
来源：数学与系统科学研究院
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