Research on mesoscale eddy-tracking algorithm of Kalman filtering under density clustering on time scale
This article proposes the tracking algorithm based on density clustering of time scale and mesoscale eddy of Kalman filtering using the fused SLA data of altimeter. Firstly, the definitive density clustering based on time scale discovers the potential association pattern between data, and screens ou...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2020-04-01
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| Series: | European Journal of Remote Sensing |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/22797254.2020.1740894 |
| _version_ | 1811262135067475968 |
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| author | Ji-Tao Li Yong-Quan Liang |
| author_facet | Ji-Tao Li Yong-Quan Liang |
| author_sort | Ji-Tao Li |
| collection | DOAJ |
| description | This article proposes the tracking algorithm based on density clustering of time scale and mesoscale eddy of Kalman filtering using the fused SLA data of altimeter. Firstly, the definitive density clustering based on time scale discovers the potential association pattern between data, and screens out the data set of mesoscale eddy trajectory. With regard to the data set with time scale conflict, it analyzes the Kalman filtering, eliminates the noise points and obtains the correct mesoscale eddy trajectory. Secondly, it turns the tracking process into an algorithm that supports batch processing by applying the data processing method to the mesoscale eddy-tracking algorithm, which solves the problem of single serialization and high time and space complexity of the traditional tracking algorithm. Based on the algorithm, this article selects the experimental data of the South China Sea for the mesoscale eddy-tracking test. The experiment turns out that the algorithm can better reveal the life course of mesoscale eddy and evolution rule of physical oceanography according to spatial scale, amplitude and eddy duration, etc. |
| first_indexed | 2024-04-12T19:18:37Z |
| format | Article |
| id | doaj.art-c3d5b194e8b34febaa0ccc33b421f114 |
| institution | Directory Open Access Journal |
| issn | 2279-7254 |
| language | English |
| last_indexed | 2024-04-12T19:18:37Z |
| publishDate | 2020-04-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | European Journal of Remote Sensing |
| spelling | doaj.art-c3d5b194e8b34febaa0ccc33b421f1142022-12-22T03:19:39ZengTaylor & Francis GroupEuropean Journal of Remote Sensing2279-72542020-04-010011010.1080/22797254.2020.17408941740894Research on mesoscale eddy-tracking algorithm of Kalman filtering under density clustering on time scaleJi-Tao Li0Yong-Quan Liang1Taishan UniversityShandong University of Science and TechnologyThis article proposes the tracking algorithm based on density clustering of time scale and mesoscale eddy of Kalman filtering using the fused SLA data of altimeter. Firstly, the definitive density clustering based on time scale discovers the potential association pattern between data, and screens out the data set of mesoscale eddy trajectory. With regard to the data set with time scale conflict, it analyzes the Kalman filtering, eliminates the noise points and obtains the correct mesoscale eddy trajectory. Secondly, it turns the tracking process into an algorithm that supports batch processing by applying the data processing method to the mesoscale eddy-tracking algorithm, which solves the problem of single serialization and high time and space complexity of the traditional tracking algorithm. Based on the algorithm, this article selects the experimental data of the South China Sea for the mesoscale eddy-tracking test. The experiment turns out that the algorithm can better reveal the life course of mesoscale eddy and evolution rule of physical oceanography according to spatial scale, amplitude and eddy duration, etc.http://dx.doi.org/10.1080/22797254.2020.1740894mesoscale eddytrackingdensity clusteringbatch processingtime complexity |
| spellingShingle | Ji-Tao Li Yong-Quan Liang Research on mesoscale eddy-tracking algorithm of Kalman filtering under density clustering on time scale European Journal of Remote Sensing mesoscale eddy tracking density clustering batch processing time complexity |
| title | Research on mesoscale eddy-tracking algorithm of Kalman filtering under density clustering on time scale |
| title_full | Research on mesoscale eddy-tracking algorithm of Kalman filtering under density clustering on time scale |
| title_fullStr | Research on mesoscale eddy-tracking algorithm of Kalman filtering under density clustering on time scale |
| title_full_unstemmed | Research on mesoscale eddy-tracking algorithm of Kalman filtering under density clustering on time scale |
| title_short | Research on mesoscale eddy-tracking algorithm of Kalman filtering under density clustering on time scale |
| title_sort | research on mesoscale eddy tracking algorithm of kalman filtering under density clustering on time scale |
| topic | mesoscale eddy tracking density clustering batch processing time complexity |
| url | http://dx.doi.org/10.1080/22797254.2020.1740894 |
| work_keys_str_mv | AT jitaoli researchonmesoscaleeddytrackingalgorithmofkalmanfilteringunderdensityclusteringontimescale AT yongquanliang researchonmesoscaleeddytrackingalgorithmofkalmanfilteringunderdensityclusteringontimescale |