Intelligent recognition and tracking algorithm based on battlefield environment

Zengying Yue; Qi Peng; Hanlin Huang; Weilong Zhang; Yang Yu; Miao Wang; Xiaolin Zhou

doi:10.1117/12.3035463

16 August 2024 Intelligent recognition and tracking algorithm based on battlefield environment

Zengying Yue, Qi Peng, Hanlin Huang, Weilong Zhang, Yang Yu, Miao Wang, Xiaolin Zhou

Proceedings Volume 13230, Third International Conference on Machine Vision, Automatic Identification, and Detection (MVAID 2024); 1323007 (2024) https://doi.org/10.1117/12.3035463
Event: Third International Conference on Machine Vision, Automatic Identification and Detection, 2024, Kunming, China

Abstract

Unmanned Aerial Vehicle (UAV) technology plays a pivotal role in military reconnaissance and battlefield surveillance. With the rapid advancement of deep learning, the integration of deep learning with UAV technology has become increasingly significant. Addressing the current shortfall in autonomous recognition capabilities of UAV technology in complex environments, this paper proposes an intelligent recognition and tracking algorithm for UAVs based on battlefield conditions. Building upon a specially curated dataset for friend-or-foe target recognition under various environments, this study combines the YOLO algorithm with PID control methods to develop a UAV control system capable of classifying target behaviors and achieving real-time tracking and ranging during dynamic flight. Notably, the friend-or-foe target recognition dataset is enhanced with multi-dimensional labels for friend-or-foe identification, enemy situation analysis, gesture control, and formation behaviors, providing a rich set of training data. Experimental results demonstrate that the target recognition classification achieved an accuracy of 91.2%, with a response time within 0.2 seconds, thereby confirming the algorithm's effectiveness and robustness under diverse battlefield conditions.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Zengying Yue, Qi Peng, Hanlin Huang, Weilong Zhang, Yang Yu, Miao Wang, and Xiaolin Zhou "Intelligent recognition and tracking algorithm based on battlefield environment", Proc. SPIE 13230, Third International Conference on Machine Vision, Automatic Identification, and Detection (MVAID 2024), 1323007 (16 August 2024); https://doi.org/10.1117/12.3035463

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KEYWORDS

Unmanned aerial vehicles

Target recognition

Detection and tracking algorithms

Control systems

Education and training

Target detection

Algorithm development

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