Study on Multipoint-Ranging-Target-Positioning Technologies for UAV

Huang, Zhengzhong; Huang, Zili; Tang, Xiangcheng; Zou, Shuoyi

doi:10.1109/eitce47263.2019.9095139

Cited by 2 publications

(1 citation statement)

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“…Wang Jianghong et al, [20], explored methods for obtaining target motion information (e.g., position, velocity, and size) during target tracking and emphasized the importance of target detection and identification techniques. Zhengzhong Huang et al, [21], proposed a target localization method based on laser ranging and solved the problem of photoelectric target consistency by image tracking, making it applicable to ground and sea surface target localization of UAVs. Yaohong Qu et al, [22], calculated the target position by solving nonlinear equations, addressed the issue that the target height value could not be accurately determined in the traditional method, and obtained the optimal UAV formation shape through simulation analysis.…”

Section: A Target Positioning Methods Based On Uavmentioning

confidence: 99%

A Dual UAV Cooperative Positioning System With Advanced Target Detection and Localization

Chang,

Pan,

et al. 2024

IEEE Access

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Utilizing Unmanned Aerial Vehicles (UAVs) plays a pivotal role in the localization of ground construction personnel targets within the specialized operational environments of the energy industry. To ensure the safety of personnel in these areas effectively, this study introduces an innovative dual UAV cooperative positioning system designed to address the challenges of personnel localization in various complex settings. In the first place, the research establishes a dual UAV collaborative remote sensing platform, specifically tailored for executing dual UAV flight control and ground personnel identification and localization tasks. Subsequently, this study proposes a high-precision ground personnel localization solution. This solution integrates the flight data of two UAVs with the pixel coordinates of targets in natural remote sensing imagery, enabling the precise localization of moving targets within complex environments. Moreover, due to the irregularity of ground personnel shapes in imagery, this research introduces an improved rotating target detection network based on the YOLOv7 architecture. This network is specifically optimized for detecting ground targets in remote sensing imagery, significantly enhancing the accuracy of target localization. Extensive experimental validation has demonstrated that this localization system can maintain target localization errors within a 5-meter threshold, effectively enhancing the safety and efficiency of personnel in specific operational areas of the energy industry.

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Section: A Target Positioning Methods Based On Uavmentioning

confidence: 99%