Multiple extended target tracking by truncated JPDA in a clutter environment
Abstract Data association is a crucial part of target tracking systems with clutter measurements. In general, its complexity increases sharply with a number of targets and measurements. Recently, high‐resolution sensors have given rise to extended target tracking problems and more than one measureme...
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| Format: | Article |
| Language: | English |
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Wiley
2021-05-01
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| Series: | IET Signal Processing |
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| Online Access: | https://doi.org/10.1049/sil2.12024 |
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| _version_ | 1832558701754449920 |
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| author | Qinlei Li Liping Song Yongquan Zhang |
| author_facet | Qinlei Li Liping Song Yongquan Zhang |
| author_sort | Qinlei Li |
| collection | DOAJ |
| description | Abstract Data association is a crucial part of target tracking systems with clutter measurements. In general, its complexity increases sharply with a number of targets and measurements. Recently, high‐resolution sensors have given rise to extended target tracking problems and more than one measurements can emerge from each target, making the association problems more complex. In this study, a tractable algorithm based on the Gaussian process measurement model and truncated joint probabilistic data association technique is proposed for multiple extended target tracking in the presence of measurement origin uncertainty. Based on the marginal association probabilities, the calculation amount is effectively reduced by truncating the association events with low probabilities in the shortest path problem. The effectiveness of the proposed algorithm is verified by the test of multiple extended targets tracking and compared with the linear‐time joint probabilistic data association as well as the algorithm on random finite sets. Simulation results show that the proposed algorithm can track multiple extended targets accurately, which is significant in high‐resolution radar tracking systems. |
| format | Article |
| id | doaj-art-fdefb29164d3489b89ffaa65a2a61277 |
| institution | Kabale University |
| issn | 1751-9675 1751-9683 |
| language | English |
| publishDate | 2021-05-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Signal Processing |
| spelling | doaj-art-fdefb29164d3489b89ffaa65a2a612772025-02-03T01:31:55ZengWileyIET Signal Processing1751-96751751-96832021-05-0115320721910.1049/sil2.12024Multiple extended target tracking by truncated JPDA in a clutter environmentQinlei Li0Liping Song1Yongquan Zhang2Department of Electronic Engineering Xidian University Xi'an ChinaDepartment of Electronic Engineering Xidian University Xi'an ChinaDepartment of Electronic Engineering Xidian University Xi'an ChinaAbstract Data association is a crucial part of target tracking systems with clutter measurements. In general, its complexity increases sharply with a number of targets and measurements. Recently, high‐resolution sensors have given rise to extended target tracking problems and more than one measurements can emerge from each target, making the association problems more complex. In this study, a tractable algorithm based on the Gaussian process measurement model and truncated joint probabilistic data association technique is proposed for multiple extended target tracking in the presence of measurement origin uncertainty. Based on the marginal association probabilities, the calculation amount is effectively reduced by truncating the association events with low probabilities in the shortest path problem. The effectiveness of the proposed algorithm is verified by the test of multiple extended targets tracking and compared with the linear‐time joint probabilistic data association as well as the algorithm on random finite sets. Simulation results show that the proposed algorithm can track multiple extended targets accurately, which is significant in high‐resolution radar tracking systems.https://doi.org/10.1049/sil2.12024filtering theoryGaussian processesprobabilityradar trackingsensor fusiontarget tracking |
| spellingShingle | Qinlei Li Liping Song Yongquan Zhang Multiple extended target tracking by truncated JPDA in a clutter environment IET Signal Processing filtering theory Gaussian processes probability radar tracking sensor fusion target tracking |
| title | Multiple extended target tracking by truncated JPDA in a clutter environment |
| title_full | Multiple extended target tracking by truncated JPDA in a clutter environment |
| title_fullStr | Multiple extended target tracking by truncated JPDA in a clutter environment |
| title_full_unstemmed | Multiple extended target tracking by truncated JPDA in a clutter environment |
| title_short | Multiple extended target tracking by truncated JPDA in a clutter environment |
| title_sort | multiple extended target tracking by truncated jpda in a clutter environment |
| topic | filtering theory Gaussian processes probability radar tracking sensor fusion target tracking |
| url | https://doi.org/10.1049/sil2.12024 |
| work_keys_str_mv | AT qinleili multipleextendedtargettrackingbytruncatedjpdainaclutterenvironment AT lipingsong multipleextendedtargettrackingbytruncatedjpdainaclutterenvironment AT yongquanzhang multipleextendedtargettrackingbytruncatedjpdainaclutterenvironment |