Vector Magnetometer Networks Outperform Scalar Networks for Undersea Surveillance

This paper addresses a practical problem in maritime surveillance, leveraging advancements in quantum magnetometers. It provides a comparative analysis of different sensor network architectures (scalar vs. vector) for target tracking. The use of an Unscented Kalman Filter (UKF) adds rigor to the analysis. The key finding, that vector networks significantly improve tracking accuracy and resilience, has direct implications for the design and deployment of undersea surveillance systems.

• •The paper investigates the application of quantum magnetometers for undersea surveillance.
• •It compares scalar and vector magnetometer network architectures.
• •Vector networks are found to be superior to scalar networks in terms of tracking accuracy and resilience.
• •An Unscented Kalman Filter is used for target tracking.