.png){kind=icon}
返回
Geomagnetic Vector Pattern Recognition Navigation Method Based on Probabilistic Neural Network
.png){kind=icon}
PRE
AI
DOI：10.1109/TGRS.2023.3273552.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Traditional geomagnetic vector matching methods are mainly based on a certain correlation criterion to filter the optimal track that the optimal track selection function is single and unable to distinguish the nonlinear mapping of the geomagnetic field and geographical position. Since the geomagnetic matching process is similar to pattern recognition, a vector pattern recognition matching method based on a probabilistic neural network (PNN) is proposed to realize geomagnetic navigation. The neural network (NN) input is geomagnetic vector elements, and the genetic algorithm is used to optimize the PNN's smooth parameter to classify better. The comparison of vector iterative closest contour point (VICCP), vector magnetic contour matching (VMAGCOM), and the proposed method is carried out in the simulation in two kinds of areas with significant and insignificant geomagnetic features. Simulation results show that the proposed method has the highest matching rates of 94% and 100% in two kinds of regions. The matching accuracy is also significantly better than traditional algorithms. Finally, the experiment is carried out to verify the effectiveness and robustness of the proposed method.
Keyword:
Navigation
Pattern matching
Biological neural networks
Training
Smoothing methods
Genetic algorithms
Fuzzy logic
Geomagnetic vector navigation
pattern recognition
probabilistic neural network (PNN) parameter optimization
期刊
IF:
8.6
论文数:
2.1W
被引数:
10.7W
机构
引用论文
The effect of a random transverse field on the critical and compensation behaviors of a nanowire
PREAI
分享收藏An overview of power topologies for micro-hydro turbines.png)
2012 3rd IEEE International Symposium on Power Electronics for Distributed Generation Systems (PEDG)
2012 3rd IEEE International Symposium on Power Electronics for Distributed Generation Systems (PEDG)IF0
PREAI
分享收藏Comparative study of soft computing techniques for mobile robot navigation in an unknown environment
PREAI
分享收藏
查看更多内容