UAV image signal transmission based on Eigenvector Analysis

Hong Wang; Yujia Yang; jingjing zhang

doi:10.1117/12.2639646

27 June 2022 UAV image signal transmission based on Eigenvector Analysis

Hong Wang, Yujia Yang, jingjing zhang

Proceedings Volume 12253, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2022); 122530T (2022) https://doi.org/10.1117/12.2639646
Event: Second International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2022), 2022, Qingdao, China

Abstract

Flight control signals of unmanned aerial vehicles (UAVs) are generally communicated by frequency hopping (FH) in spread spectrum mode. The detection method based on the back-end signal processing can not be widely used in frequency hopping signal detection and identification under different parameters, and has no practical value in engineering. In view of the above problems, this paper proposes a UAV communication technology based on image signal transmission, whose core content is sliding shift cyclic autocorrelation. The technology extracts the periodic characteristics of the internal cyclic prefix of OFDM signal, and establishes the characteristic database of multiple UAVs and Wi-Fi in advance. Compared with the traditional method, the recognition rate of the proposed method is 6. 74% higher than that of other methods, and the blind detection algorithm is 3. 1% better than that of other methods. It is verified that the proposed method can effectively prevent and solve the problems of frequency offset, system instruction update and surrounding electromagnetic interference. It contributes to the improvement of UAV signal transmission speed and performance.

Citation Download Citation

Hong Wang, Yujia Yang, and jingjing zhang "UAV image signal transmission based on Eigenvector Analysis", Proc. SPIE 12253, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2022), 122530T (27 June 2022); https://doi.org/10.1117/12.2639646

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KEYWORDS

Detection and tracking algorithms

Unmanned aerial vehicles

Image transmission

Signal to noise ratio

Signal detection

Image segmentation

Image processing algorithms and systems

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