4.7 Article

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

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIM.2020.3034966

关键词

Bionic geomagnetic navigation; evolutionary algorithm; geomagnetic field (GF); multiobjective optimization; navigation path searching

资金

  1. National Natural Science Foundation of China [52071080]
  2. Inertial Technology Key Lab Fund [614250607011709]
  3. Fundamental Research Funds for the Central Universities [2242020k1G009]
  4. Key Laboratory Fund for Underwater Information and Control [614221805051809]
  5. Jiangsu Key Laboratory Fund for Green Ship Technology [2019Z01]
  6. Remaining Funds Cultivation Project of National Natural Science Foundation of Southeast University [9S20172204]

向作者/读者索取更多资源

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

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据