Nonlinear dynamics design and operation of advanced magnetic sensors

Magnetic sensors are inherently nonlinear systems, which have assisted mankind in detecting weak magnetic signals for a wide variety of applications. For instance: biomedical tracking of magnetic particles, e.g., MRI machines commonly used for diagnosing multiple sclerosis, brain tumors, and spinal infections; geological equipment, e.g., NASA explorers: homeland defense, e.g., detection of mines and explosives. Using ideas and methods from nonlinear dynamics research in Engineering, Mathematics, and Physics, we show that higher sensitivity, lower power consumption, and reduced costs, can all be achieved through an integrating approach that combines a new sensing technique, the Residence Times Detection (RTD), with a novel Network Sensor Architecture, where the power of multiple sensors is integrated into a single system. We demonstrate that under the proposed approach, fluxgates magnetometers, in particular, can become very competitive against the most sensitive of all sensors, the SQUID (Superconducting Quantum Interference Devices), at a fraction of the cost and size of SQUIDs. The ideas are model-independent, so they can be used to enhance the performance of many other type of sensors such as electric field sensors and gyroscopes.