Research on radar recognition technology for UAV target in migratory birds background

Haibo Liu*, Xingkai Wu, Guangmao Chen

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

Abstract

In recent years, the unmanned aerial vehicle (UAV) has emerged as a significant risk factor in the field of low-altitude safety. Radar technology plays a crucial role in the detection of UAV within low-altitude airspace. During radar detection, avian targets, particularly migratory birds, share similarities with UAV in terms of flight characteristics, such as flight altitude, flight speed, course stability, radar cross-section, making it very difficult to distinguish UAV target from bird targets. In this paper, the flight mechanisms of UAV and migratory birds are analyzed, and a spatial migration intensity perception algorithm based on the trajectory is proposed. The target flight characteristics and spatial correlation characteristics are extracted from recent and historical radar trajectory data. The results of spatial migration intensity perception are combined with various trajectory characteristics, and five machine learning algorithms are used to realize the accurate recognition of UAV targets and birds. Finally, the effectiveness of the algorithm is verified by experimental data.

Original languageEnglish
Pages (from-to)1055-1062
Number of pages8
JournalIET Conference Proceedings
Volume2023
Issue number47
DOIs
Publication statusPublished - 2023
EventIET International Radar Conference 2023, IRC 2023 - Chongqing, China
Duration: 3 Dec 20235 Dec 2023

Keywords

  • feature extraction
  • machine learning
  • migration birds
  • Radar target recognition

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