Master Thesis: Drone Detection with Acoustic and ISAC Sensing

Teknik, data och digitalt · Data, AI och analys · Datavetenskap · Maskininlärning

I korthet

This Master Thesis project focuses on utilizing AI for drone detection by combining acoustic and Integrated Sensing and Communication (ISAC) technologies. You will explore how these complementary sensing methods can improve detection, classification, and tracking of drones, leading to recommendations for future multi-modal sensing systems.

Ansvarsområden

Investigate acoustic sensing and ISAC as complementary technologies for drone detection.
Compare detection performance, extractable information, and ideal operating conditions for acoustic vs. ISAC sensing.
Record and analyze drone acoustic signatures, and experiment with microphone arrays and direction-finding.
Classify drones from their sound and use acoustic cues to identify a drone after an ISAC detection event.
Explore AI for detection, classification, and sensor fusion, including combining confidence from different modalities.
Evaluate cost-versus-performance trade-offs for sensing systems.
Develop a set of recommendations for future AI-enabled, multi-modal drone sensing systems.

Krav

Knowledge in Computer Science, Electrical Engineering, Signal Processing, or a related field.
Experience in at least one programming language (Python is preferred).
Eagerness to learn and explore new concepts.

Önskade kvalifikationer

Bonus: experience in machine learning, signal processing, or wireless/acoustic systems.

Förmåner

Opportunity to define areas of exploration within the project.
Work with cutting-edge AI and sensing technologies.

Färdigheter

PythonMachine LearningSignal ProcessingAI

#AI#Drone Detection#Acoustic Sensing#ISAC#Signal Processing#Machine Learning#Master Thesis

Om Ericsson

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