Bio-Inspired Magnetic Field Sensing and Processing

Several animals use the Earth's magnetic field in concert with other sensor modes for local and continental-scale navigation tasks. Simultaneously, Earth's magnetic field offers a signal that engineered systems can leverage for navigating in environments where GPS is unavailable or unreliable. In addition, many animal sensory systems use a distributed sensing paradigm where a number of sensors are used to collect data, while the animal's nervous system processes and fuses data to generate behavioral commands in a robust manner. Building on these notions and existing biological studies, our work investigates biologically-inspired distributed magnetic sensing to use Earth's magnetic field for navigation. We use biologically derived and inspired methods such as neuronal population models to process and interpret the distributed data. In addition to bio-inspired methods, we explore using engineering-based methods to process and interpret data for the purposes of reference and comparison. As expected, with all methods, an increase in the number of sensors provides enhanced robustness to sensor noise. Preliminary work indicates that neuronal population models offer potential benefits in terms of noise removal from a signal. Our goal is to leverage neuronal models to agilely and robustly fuse data from multiple sensors and sensor modes for enhanced navigation performance.