Geomagnetic Gradient-Assisted Evolutionary Algorithm for Long-Range Underwater Navigation

Extensive research results have shown that animals like pigeons and turtles can use geomagnetic information for long-distance migration homing. This article studies the bionic navigation method inspired by magnetotaxis behavior without prior knowledge. The problem of is generalized as an autonomous search path under excitation environment. gradient-assisted evolutionary algorithm long-range underwater proposed. In order to optimize path, heading angle predicted gradient used constrain sample space in algorithm. Then, according principle multiparameter simultaneous convergence, evaluation function improved enhance reliability accuracy path. Simulations before after improvement are carried out based on data retrieved from enhanced magnetic model (EMM). performance evaluated verified case area with normal field (GF), anomaly area, multiple destinations. simulation show efficiency straightness greatly improved. reason constraint reduces randomness process search, evaluate quality samples more accurately. also has good which indicates potential application future.