Tracking Multiple Unmanned Aerial Vehicles through Occlusion in Low-Altitude Airspace
In an intelligent multi-target tracking (MTT) system, the tracking filter cannot track multi-targets significantly through occlusion in a low-altitude airspace. The most challenging issues are the target deformation, target occlusion and targets being concealed by the presence of background clutter....
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-03-01
|
| Series: | Drones |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2504-446X/7/4/241 |
| _version_ | 1797605736583266304 |
|---|---|
| author | Sufyan Ali Memon Hungsun Son Wan-Gu Kim Abdul Manan Khan Mohsin Shahzad Uzair Khan |
| author_facet | Sufyan Ali Memon Hungsun Son Wan-Gu Kim Abdul Manan Khan Mohsin Shahzad Uzair Khan |
| author_sort | Sufyan Ali Memon |
| collection | DOAJ |
| description | In an intelligent multi-target tracking (MTT) system, the tracking filter cannot track multi-targets significantly through occlusion in a low-altitude airspace. The most challenging issues are the target deformation, target occlusion and targets being concealed by the presence of background clutter. Thus, the true tracks that follow the desired targets are often lost due to the occlusion of uncertain measurements detected by a sensor, such as a motion capture (mocap) sensor. In addition, sensor measurement noise, process noise and clutter measurements degrade the system performance. To avoid track loss, we use the Markov-chain-two (MC2) model that allows the propagation of target existence through the occlusion region. We utilized the MC2 model in linear multi-target tracking based on the integrated probabilistic data association (LMIPDA) and proposed a modified integrated algorithm referred to here as LMIPDA-MC2. We consider a three-dimensional surveillance for tracking occluded targets, such as unmanned aerial vehicles (UAVs) and other autonomous vehicles at low altitude in clutters. We compared the results of the proposed method with existing Markov-chain model based algorithms using Monte Carlo simulations and practical experiments. We also provide track retention and false-track discrimination (FTD) statistics to explain the significance of the LMIPDA-MC2 algorithm. |
| first_indexed | 2024-03-11T05:05:18Z |
| format | Article |
| id | doaj.art-a7ebf64674f546bc8ec70bebbc3e854d |
| institution | Directory Open Access Journal |
| issn | 2504-446X |
| language | English |
| last_indexed | 2024-03-11T05:05:18Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Drones |
| spelling | doaj.art-a7ebf64674f546bc8ec70bebbc3e854d2023-11-17T18:57:59ZengMDPI AGDrones2504-446X2023-03-017424110.3390/drones7040241Tracking Multiple Unmanned Aerial Vehicles through Occlusion in Low-Altitude AirspaceSufyan Ali Memon0Hungsun Son1Wan-Gu Kim2Abdul Manan Khan3Mohsin Shahzad4Uzair Khan5Department of Defense Systems Engineering, Sejong University, Seoul 05006, Republic of KoreaDepartment of Mechanical Engineering, Ulsan National Institute of Science and Technology, Ulsan 44919, Republic of KoreaMaritime Security and Safety Research Center, Korea Institute of Ocean Science and Technology, Busan 49111, Republic of KoreaDepartment of Mechanical and Aerospace Engineering, Bristol University, Bristol BS8 1QU, UKDepartment of Electrical and Computer Engineering, COMSATS University Islamabad, Abbottabad Campus, Abbottabad 22060, PakistanDepartment of Electrical and Computer Engineering, COMSATS University Islamabad, Abbottabad Campus, Abbottabad 22060, PakistanIn an intelligent multi-target tracking (MTT) system, the tracking filter cannot track multi-targets significantly through occlusion in a low-altitude airspace. The most challenging issues are the target deformation, target occlusion and targets being concealed by the presence of background clutter. Thus, the true tracks that follow the desired targets are often lost due to the occlusion of uncertain measurements detected by a sensor, such as a motion capture (mocap) sensor. In addition, sensor measurement noise, process noise and clutter measurements degrade the system performance. To avoid track loss, we use the Markov-chain-two (MC2) model that allows the propagation of target existence through the occlusion region. We utilized the MC2 model in linear multi-target tracking based on the integrated probabilistic data association (LMIPDA) and proposed a modified integrated algorithm referred to here as LMIPDA-MC2. We consider a three-dimensional surveillance for tracking occluded targets, such as unmanned aerial vehicles (UAVs) and other autonomous vehicles at low altitude in clutters. We compared the results of the proposed method with existing Markov-chain model based algorithms using Monte Carlo simulations and practical experiments. We also provide track retention and false-track discrimination (FTD) statistics to explain the significance of the LMIPDA-MC2 algorithm.https://www.mdpi.com/2504-446X/7/4/241detectiondata associationfalse-track discrimination (FTD)multi-target tracking (MTT)Markov chain model 2 (MC2)probability of target existence (PTE) |
| spellingShingle | Sufyan Ali Memon Hungsun Son Wan-Gu Kim Abdul Manan Khan Mohsin Shahzad Uzair Khan Tracking Multiple Unmanned Aerial Vehicles through Occlusion in Low-Altitude Airspace Drones detection data association false-track discrimination (FTD) multi-target tracking (MTT) Markov chain model 2 (MC2) probability of target existence (PTE) |
| title | Tracking Multiple Unmanned Aerial Vehicles through Occlusion in Low-Altitude Airspace |
| title_full | Tracking Multiple Unmanned Aerial Vehicles through Occlusion in Low-Altitude Airspace |
| title_fullStr | Tracking Multiple Unmanned Aerial Vehicles through Occlusion in Low-Altitude Airspace |
| title_full_unstemmed | Tracking Multiple Unmanned Aerial Vehicles through Occlusion in Low-Altitude Airspace |
| title_short | Tracking Multiple Unmanned Aerial Vehicles through Occlusion in Low-Altitude Airspace |
| title_sort | tracking multiple unmanned aerial vehicles through occlusion in low altitude airspace |
| topic | detection data association false-track discrimination (FTD) multi-target tracking (MTT) Markov chain model 2 (MC2) probability of target existence (PTE) |
| url | https://www.mdpi.com/2504-446X/7/4/241 |
| work_keys_str_mv | AT sufyanalimemon trackingmultipleunmannedaerialvehiclesthroughocclusioninlowaltitudeairspace AT hungsunson trackingmultipleunmannedaerialvehiclesthroughocclusioninlowaltitudeairspace AT wangukim trackingmultipleunmannedaerialvehiclesthroughocclusioninlowaltitudeairspace AT abdulmanankhan trackingmultipleunmannedaerialvehiclesthroughocclusioninlowaltitudeairspace AT mohsinshahzad trackingmultipleunmannedaerialvehiclesthroughocclusioninlowaltitudeairspace AT uzairkhan trackingmultipleunmannedaerialvehiclesthroughocclusioninlowaltitudeairspace |