Research on Signal Detection Methods for Drones in Complex Pendulum Environment

DOI

10.2991/978-94-6463-540-9_45How to use a DOI?

Keywords

Drones; Complex Electromagnetic Environment; Signal Detection Technology

Abstract

In recent years, drones have been widely used in various industries and have played a significant role. However, with the popularization of civilian drones, the safety issues brought about by drone “black flying” should also be given sufficient attention. Good drone signal detection technology is a prerequisite for achieving drone supervision. As a non cooperative recipient, it is necessary to detect, estimate parameters, identify modulation, and identify protocol for the received drone communication signals. Compared to large or military drones, most small civilian drones use radio frequency signal based wireless monitoring technology. This technology uses radio frequency signals between the drone and the remote control for drone detection, which has strong concealment and all-weather advantages. However, this technology still has the following problems: (1) Small civilian drones generally have lower signal transmission power, and the signal reception section can receive weaker signals at long distances. (2) In complex environments, especially in cities, the noise interference and co frequency interference caused by the complex electromagnetic environment make it difficult to identify the signal band received by the receiving end. This article mainly studies the ability to accurately detect signals emitted by drones under complex electromagnetic interference conditions and weak signal frequencies.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

TY  - CONF
AU  - Linjia Zhang
PY  - 2024
DA  - 2024/10/16
TI  - Research on Signal Detection Methods for Drones in Complex Pendulum Environment
BT  - Proceedings of the 2024 2nd International Conference on Image, Algorithms and Artificial Intelligence (ICIAAI 2024)
PB  - Atlantis Press
SP  - 456
EP  - 462
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-540-9_45
DO  - 10.2991/978-94-6463-540-9_45
ID  - Zhang2024
ER  -