Improved RefineDet Network Assisted by Time Frequency Characteristics for UAV Signal Recognition

Yuan Zhao, Jian Zhang, Meng Zhu, Chengkai Tang, Zesheng Dan, Lejing Ma

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The unmanned aerial vehicle (UAV) signal detection method based on time-frequency spectrum has the problems of low success rate and difficulty in detecting small target signals in time-frequency spectrum. Combining theoretical knowledge related to deep learning, an intelligent perception and recognition method based on UAV telemetry command signals is proposed. Firstly, the linear STFT time-frequency analysis method and nonlinear SPWVD time-frequency analysis method are combined to balance the time-frequency resolution and avoid the cross terms. An improved RefineDet network with an Intersection over Union is proposed to solve the problem of mismatch between prediction box and classification. Finally, an UAV identification platform is built. Experiment results demonstrate that the proposed network can achieve high recognition accuracy in multi-objective UAV scenarios.

Original languageEnglish
Title of host publicationProceedings of 2023 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350316728
DOIs
StatePublished - 2023
Event2023 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2023 - Zhengzhou, Henan, China
Duration: 14 Nov 202317 Nov 2023

Publication series

NameProceedings of 2023 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2023

Conference

Conference2023 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2023
Country/TerritoryChina
CityZhengzhou, Henan
Period14/11/2317/11/23

Keywords

  • RefineDet network
  • Stft-SPWVD
  • UAV

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