An Improved Multiple-Target Tracking Scheme Based on IGGM–PMBM for Mobile Aquaculture Sensor Networks
The Poisson multi-Bernoulli Mixture (PMBM) filter, as well as its variants, is a popular and practical multitarget tracking algorithm. There are some pending problems for the standard PMBM filter, such as unknown detection probability, random target newborn distribution, and high energy consumption...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-01-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/13/2/926 |
| _version_ | 1797446647784931328 |
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| author | Chunfeng Lv Jianping Zhu Naixue Xiong Zhengsu Tao |
| author_facet | Chunfeng Lv Jianping Zhu Naixue Xiong Zhengsu Tao |
| author_sort | Chunfeng Lv |
| collection | DOAJ |
| description | The Poisson multi-Bernoulli Mixture (PMBM) filter, as well as its variants, is a popular and practical multitarget tracking algorithm. There are some pending problems for the standard PMBM filter, such as unknown detection probability, random target newborn distribution, and high energy consumption for limited computational and processing capacity in sensor networks. For the sake of accommodating these existing problems, an improved multitarget tracking method based on a PMBM filter with adaptive detection probability and adaptive newborn distribution is proposed, accompanied by an associated distributed fusion strategy to reduce the computational complexities. Firstly, gamma (GAM) distribution is introduced to present the augmented state of unknown and changing target detection probability. Secondly, the intensity of newborn targets is adaptively derived from the inverse gamma (IG) distribution based on this augmented state. Then, the measurement likelihood is presented as a gamma distribution for the augmented state. On these bases, the detailed recursion and closed-form solutions to the proposed filter are derived by means of approximating the intensity of target birth and potential targets to an inverse gamma Gaussian mixture (IGGM) form and the density of existing Bernoulli components to a single IGGM form. Moreover, the associated distributed fusion strategy generalized covariance intersection (GCI), whose target states are measured by multiple sensors according to their respective fusion weights, is applied to a large-scale aquaculture tracking network. Comprehensive experiments are presented to verify the effectiveness of this IGGM–PMBM method, and comparisons with other multitarget tracking filters also demonstrate that tracking behaviors are largely improved; in particular, tracking energy consumption is reduced sharply, and tracking accuracy is relatively enhanced. |
| first_indexed | 2024-03-09T13:43:34Z |
| format | Article |
| id | doaj.art-b9d9497259464cc09f16f92ae5141abf |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-09T13:43:34Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-b9d9497259464cc09f16f92ae5141abf2023-11-30T21:03:38ZengMDPI AGApplied Sciences2076-34172023-01-0113292610.3390/app13020926An Improved Multiple-Target Tracking Scheme Based on IGGM–PMBM for Mobile Aquaculture Sensor NetworksChunfeng Lv0Jianping Zhu1Naixue Xiong2Zhengsu Tao3SOU College of Engineering Science and Technology, Shanghai Ocean University, No. 999, Huchenghuan Road, Shanghai 201306, ChinaSOU College of Engineering Science and Technology, Shanghai Ocean University, No. 999, Huchenghuan Road, Shanghai 201306, ChinaDepartment of Computer, Mathematical and Physical Sciences, Sul Ross State University, Alpine, TX 79830, USADepartment of Electronic, Information and Electrical Engineering, Shanghai Jiaotong University, No. 800, Dongchuan Road, Shanghai 200240, ChinaThe Poisson multi-Bernoulli Mixture (PMBM) filter, as well as its variants, is a popular and practical multitarget tracking algorithm. There are some pending problems for the standard PMBM filter, such as unknown detection probability, random target newborn distribution, and high energy consumption for limited computational and processing capacity in sensor networks. For the sake of accommodating these existing problems, an improved multitarget tracking method based on a PMBM filter with adaptive detection probability and adaptive newborn distribution is proposed, accompanied by an associated distributed fusion strategy to reduce the computational complexities. Firstly, gamma (GAM) distribution is introduced to present the augmented state of unknown and changing target detection probability. Secondly, the intensity of newborn targets is adaptively derived from the inverse gamma (IG) distribution based on this augmented state. Then, the measurement likelihood is presented as a gamma distribution for the augmented state. On these bases, the detailed recursion and closed-form solutions to the proposed filter are derived by means of approximating the intensity of target birth and potential targets to an inverse gamma Gaussian mixture (IGGM) form and the density of existing Bernoulli components to a single IGGM form. Moreover, the associated distributed fusion strategy generalized covariance intersection (GCI), whose target states are measured by multiple sensors according to their respective fusion weights, is applied to a large-scale aquaculture tracking network. Comprehensive experiments are presented to verify the effectiveness of this IGGM–PMBM method, and comparisons with other multitarget tracking filters also demonstrate that tracking behaviors are largely improved; in particular, tracking energy consumption is reduced sharply, and tracking accuracy is relatively enhanced.https://www.mdpi.com/2076-3417/13/2/926multitarget point trackingPMBM filterGCI fusionIGGM implementationaquaculture |
| spellingShingle | Chunfeng Lv Jianping Zhu Naixue Xiong Zhengsu Tao An Improved Multiple-Target Tracking Scheme Based on IGGM–PMBM for Mobile Aquaculture Sensor Networks Applied Sciences multitarget point tracking PMBM filter GCI fusion IGGM implementation aquaculture |
| title | An Improved Multiple-Target Tracking Scheme Based on IGGM–PMBM for Mobile Aquaculture Sensor Networks |
| title_full | An Improved Multiple-Target Tracking Scheme Based on IGGM–PMBM for Mobile Aquaculture Sensor Networks |
| title_fullStr | An Improved Multiple-Target Tracking Scheme Based on IGGM–PMBM for Mobile Aquaculture Sensor Networks |
| title_full_unstemmed | An Improved Multiple-Target Tracking Scheme Based on IGGM–PMBM for Mobile Aquaculture Sensor Networks |
| title_short | An Improved Multiple-Target Tracking Scheme Based on IGGM–PMBM for Mobile Aquaculture Sensor Networks |
| title_sort | improved multiple target tracking scheme based on iggm pmbm for mobile aquaculture sensor networks |
| topic | multitarget point tracking PMBM filter GCI fusion IGGM implementation aquaculture |
| url | https://www.mdpi.com/2076-3417/13/2/926 |
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