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Tracking Strategy of Unmanned Aerial Vehicle for Tracking Moving Target

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  • Robot and Applications
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Abstract

Unmanned aerial vehicles (UAVs) are prone to losing their targets when tracking moving objectives. A tracking strategy is proposed herein that enables the standoff tracking of a moving target using a vision system, which significantly reduces the occurrence of target loss. The strategy combines the Gimbal Control Algorithm based on Motion Compensation (GCAMC) with the Improved Reference Point Guidance Method (IRPGM). The GCAMC utilizes the attitude of the UAV and the deviation of the target from image center as the feedback. The target can be kept within the field-of-view (FOV) of the camera when the gimbal model is unknown. The IRPGM generates straight or circular paths according to the speed and potition of the target, while the UAV will continuously track the generated trajectory to achieve the objective of target tracking. To validate and demonstrate the tracking performance of the proposed strategy, a closed-loop visual simulation platform was devised and implemented to simulate the process of target tracking. The results of the simulation demonstrate that by using the proposed approach, the UAV can enter the desired trajectory quickly when its initial position and flight direction are arbitrary.

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Authors and Affiliations

  1. School of Automation, Northwestern Polytechnical University, Xi’an, Shannxi, 710129, China

    Chuanjian Lin, Weiguo Zhang & Jingping Shi

  2. Shaanxi Province Key Laboratory of Flight Control and Simulation Technology, Xi’an, Shannxi, 710129, China

    Jingping Shi

Authors
  1. Chuanjian Lin
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  2. Weiguo Zhang
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  3. Jingping Shi
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Corresponding author

Correspondence to Chuanjian Lin.

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Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This journal was supported by the National Natural Science Foundation of China (No. 61573286), the Fundamental Research Funds for the Central Universities(3102019ZDHKY07), and Shaanxi Province Key Laboratory of Flight Control and Simulation Technology.

Chuanjian Lin received his B.S. degree in Automation from Northwestern Polytechnical University in 2017. He is currently pursing a Ph.D degree in Control Science and Engineering with Northwestern Polytechnical University. His research interests include target detection, target tracking, and flight guidance.

Weiguo Zhang is a Professor at the School of Automation, Northwestern Polytechnical University. He received his Ph.D. degree in Control Science and Engineering from Northwestern Polytechnical University in 1997. His research interests include modern control methods, fault tolerant control method, adaptive control, and advanced and intelligent flight control.

Jingping Shi is an Associate Professor at the School of Automation, Northwestern Polytechnical University. He received his Ph.D. degree in Control Science and Engineering from Northwestern Polytechnical University in 2009. His research interests include flight control, path planning, and control allocation.

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Lin, C., Zhang, W. & Shi, J. Tracking Strategy of Unmanned Aerial Vehicle for Tracking Moving Target. Int. J. Control Autom. Syst. 19, 2183–2194 (2021). https://doi.org/10.1007/s12555-020-2049-4

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  • DOI: https://doi.org/10.1007/s12555-020-2049-4

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