Bio-Inspired Approach for Long-Range Underwater Navigation Using Model Predictive Control

Lots of evidence has indicated that many kinds of animals can achieve goal-oriented navigation by spatial cognition and dead reckoning. The geomagnetic field (GF) is a ubiquitous cue for navigation by these animals. Inspired by the goal-oriented navigation of animals, a novel long-distance underwater geomagnetic navigation (LDUGN) method is presented in this article, which only utilizes the declination component (D) and inclination component (I) of GF for underwater navigation without any prior knowledge of the geographical location or geomagnetic map. The D and I measured by high-precision geomagnetic sensors are compared periodically with that of the destination to determine the velocity and direction in the next step. A model predictive control (MPC) algorithm with control and state constraints is proposed to achieve the control and optimization of navigation trajectory. Because the optimal control is recalculated at each sampling instant, the MPC algorithm can overcome interferences of geomagnetic daily fluctuation, geomagnetic storms, ocean current, and geomagnetic local anomaly. The simulation results validate the feasibility and accuracy of the proposed algorithm.