Signal Processing Techniques for Drone Detection

  • Unique Paper ID: 161392
  • Volume: 10
  • Issue: 3
  • PageNo: 504-512
  • Abstract:
  • Drones have garnered great popularity due to their widespread applications across various industries, ranging from surveillance and reconnaissance to logistics and entertainment. However, the increasing use of drones has also given platform to potential security threat activities, such as unauthorized surveillance, smuggling, and privacy invasion. As a result, there is need to develop efficient and reliable drone detection systems to safeguard sensitive areas and public spaces. This paper focuses on the development and implementation of an inclusive drone detection system based on advanced signal processing techniques and machine learning algorithms and deep learning algorithms. The proposed system aims to identify and classify drones with highest accuracy on real world datasets. Using the real-world datasets and different highly accurate techniques for classification the model developed is reliable and can be directly used for advance practical purposes.

Copyright & License

Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

BibTeX

@article{161392,
        author = {Manan Jandial and Teekshan Heera and Deepak Gupta and Bhawna Sharma and Sheetal Gandotra},
        title = {Signal Processing Techniques for Drone Detection},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {10},
        number = {3},
        pages = {504-512},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=161392},
        abstract = {Drones have garnered great popularity due to their widespread applications across various industries, ranging from surveillance and reconnaissance to logistics and entertainment. However, the increasing use of drones has also given platform to potential security threat activities, such as unauthorized surveillance, smuggling, and privacy invasion. As a result, there is need to develop efficient and reliable drone detection systems to safeguard sensitive areas and public spaces. This paper focuses on the development and implementation of an inclusive drone detection system based on advanced signal processing techniques and machine learning algorithms and deep learning algorithms. The proposed system aims to identify and classify drones with highest accuracy on real world datasets. Using the real-world datasets and different highly accurate techniques for classification the model developed is reliable and can be directly used for advance practical purposes.  },
        keywords = {},
        month = {},
        }

Cite This Article

  • ISSN: 2349-6002
  • Volume: 10
  • Issue: 3
  • PageNo: 504-512

Signal Processing Techniques for Drone Detection

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