Proceedings of the International Conference on Intelligent Systems for a Sustainable Future (ISSF 2026)

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EMI Resilient Drone Navigation System

Authors
J. Ramprabu1, *, B. Shirish Aravind2, B. Shri Ram3, R. P. Hariharan4, B. Rishya Vandhiyan5, N. Vinoth Kumar6
1Assistant Professor II, Department of Electrical And Electronics Engineering, Kumaraguru College of Technology, Coimbatore, India
2B.E. Electrical and Electronics Engineering, Kumaraguru College of Technology, Coimbatore, India
3B.E. Electrical and Electronics Engineering, Kumaraguru College of Technology, Coimbatore, India
4B.E. Electrical and Electronics Engineering, Kumaraguru College of Technology, Coimbatore, India
5B.E. Electrical and Electronics Engineering, Kumaraguru College of Technology, Coimbatore, India
6Associate Professor, Department of Electrical And Electronics Engineering, Kumaraguru College of Technology, Coimbatore, India
*Corresponding author. Email: ramprabu.j.eee@kct.ac.in
Corresponding Author
J. Ramprabu
Available Online 16 June 2026.
DOI
10.2991/978-94-6239-693-7_47How to use a DOI?
Keywords
UAVs; EMI; IMU; FC and GPS
Abstract

Unmanned Aerial Vehicles (UAVs) or specifically drones are commonly used in monitoring and delivery applications. Due to their versatile characteristics in many sectors, they are also used in all environments, which also include EMI prone zones. Zones which are surrounding transmission / power lines are considered as an EMI prone zone. EMI interferes with the switching logics and communication links thereby tampering with the stability of the drone. EMI can tamper with drone components like flight controller (FC), inertial measurement unit (IMU) and GPS module, causing unstable flight, navigation errors, and thereby loss of control. To navigate these issues, a system based on sensor-based EMI resilient navigation is proposed which can detect EMI from various directions and navigate the drone towards the path with least EMI, therefore allowing the drone to operate near EMI prone zones safely and autonomously. The system utilizes various sensors to continuously monitor the amplitude and direction of EMI during flight. When the detected EMI level exceeds a threshold, the sensor feedback allows the FC to designate a path with the least EMI and changes the drone’s trajectory thereby moving the drone away from interference prone zones. A simulation is developed using SIMULINK to model the harmonics caused by the EMI, drone’s navigation behavior with respect to the EMI levels and navigation planning.

Copyright
© 2026 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.

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Volume Title
Proceedings of the International Conference on Intelligent Systems for a Sustainable Future (ISSF 2026)
Series
Atlantis Highlights in Intelligent Systems
Publication Date
16 June 2026
ISBN
978-94-6239-693-7
ISSN
2589-4919
DOI
10.2991/978-94-6239-693-7_47How to use a DOI?
Copyright
© 2026 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.

Cite this article

risenwbib
TY  - CONF
AU  - J. Ramprabu
AU  - B. Shirish Aravind
AU  - B. Shri Ram
AU  - R. P. Hariharan
AU  - B. Rishya Vandhiyan
AU  - N. Vinoth Kumar
PY  - 2026
DA  - 2026/06/16
TI  - EMI Resilient Drone Navigation System
BT  - Proceedings of the International Conference on Intelligent Systems for a Sustainable Future (ISSF 2026)
PB  - Atlantis Press
SP  - 486
EP  - 491
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6239-693-7_47
DO  - 10.2991/978-94-6239-693-7_47
ID  - Ramprabu2026
ER  -