A Novel Adaptive Noise Covariance Matrix Estimation and Filtering Method: Application to Multiobject Tracking
文献类型：期刊论文
| 作者 | Jiang, Chao1,2,6; Wang, Zhiling3,5,7 ; Liang, Huawei3,5,7; Wang, Yajun4
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| 刊名 | IEEE TRANSACTIONS ON INTELLIGENT VEHICLES
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| 出版日期 | 2024 |
| 卷号 | 9 |
| 关键词 | Covariance matrices Noise measurement Estimation Correlation Filtering Calibration Technological innovation Kalman filtering adaptive estimation process and measurement noise covariance matrices multiobject tracking |
| ISSN号 | 2379-8858 |
| DOI | 10.1109/TIV.2023.3286979 |
| 通讯作者 | Jiang, Chao(jc2009@mail.ustc.edu.cn) |
| 英文摘要 | This article presents a novel online adaptive method for estimating the process and measurement noise covariance matrices in Kalman filters (KFs) to address the challenge of varying noise characteristics in practical applications. Specifically, the proposed method decomposes the noise covariance matrix into an element distribution matrix and a noise intensity and employs an improved Sage filter to estimate the element distribution matrix. Additionally, a calibration and correction method is introduced to accurately determine and adaptively correct the online bias of the noise intensity. The unbiasedness and convergence of the proposed method are mathematically proven under the condition that the system is detectable. Moreover, this method is applied to multiobject tracking (MOT) based on KFs and light detection and ranging (LiDAR), and it is evaluated on the KITTI dataset and the official KITTI server. The experimental results demonstrate that the proposed method achieves significantly improved MOT performance based on KFs and outperforms other LiDAR-based methods on the KITTI leaderboard. This method provides a new approach for enhancing the performance of KFs and assisting with MOT, and it has practical feasibility for real-world applications. |
| WOS关键词 | KALMAN FILTER |
| 资助项目 | National Key Research and Development Program of China[2020AAA0108103] ; Key Science and Technology Project of Anhui[202103a05020007] |
| WOS研究方向 | Computer Science ; Engineering ; Transportation |
| 语种 | 英语 |
| WOS记录号 | WOS:001173317800060 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 资助机构 | National Key Research and Development Program of China ; Key Science and Technology Project of Anhui |
| 源URL | [http://ir.hfcas.ac.cn:8080/handle/334002/136166]  |
| 专题 | 中国科学院合肥物质科学研究院 |
| 通讯作者 | Jiang, Chao |
| 作者单位 | 1.Univ Sci & Technol China, Hefei 230026, Peoples R China 2.Hefei Inst Phys Sci, Chinese Acad Sci, Hefei 230031, Peoples R China 3.Anhui Engn Lab Intelligent Driving Technol & Appl, Hefei 230031, Peoples R China 4.Univ South China, Sch Elect Engn, Hengyang 421001, Peoples R China 5.Chinese Acad Sci, Innovat Res Inst Robot & Intelligent Mfg, Hefei 230031, Peoples R China 6.Univ South China, Hengyang 421001, Peoples R China 7.Chinese Acad Sci, Hefei Inst Phys Sci, Hefei 230031, Peoples R China |
| 推荐引用方式 GB/T 7714 | Jiang, Chao,Wang, Zhiling,Liang, Huawei,et al. A Novel Adaptive Noise Covariance Matrix Estimation and Filtering Method: Application to Multiobject Tracking[J]. IEEE TRANSACTIONS ON INTELLIGENT VEHICLES,2024,9. |
| APA | Jiang, Chao,Wang, Zhiling,Liang, Huawei,&Wang, Yajun.(2024).A Novel Adaptive Noise Covariance Matrix Estimation and Filtering Method: Application to Multiobject Tracking.IEEE TRANSACTIONS ON INTELLIGENT VEHICLES,9. |
| MLA | Jiang, Chao,et al."A Novel Adaptive Noise Covariance Matrix Estimation and Filtering Method: Application to Multiobject Tracking".IEEE TRANSACTIONS ON INTELLIGENT VEHICLES 9(2024). |
入库方式： OAI收割
来源：合肥物质科学研究院
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