104 bis - Q-PAD AI FOR ANOMALY DETECTION IN MULTI-SENSOR PNT

The main objective of this project is to develop an anomaly detection framework specifically tailored for Nitrogen-Vacancy (NV) quantum sensor systems in Position, Naviga-tion, and Timing (PNT) applications. This framework will fuse data from both quantum and classical sensors, with particular attention to detecting inherent quantum sensor anomalies. The system will employ AI-driven methodologies to process and analyse multi-sensor data streams, aiming to outperform conventional machine learning approaches in PNT applications.
 
 The technical implementation consists of three main phases:
 1. Simulation environment development
 2. Hardware integration and sensor fusion
 3. Adaptive sensor fusion algorithm