基于新型分层邻域阈值搜索法提高水下潜器重力匹配导航的匹配效率

本文开展了水下潜器重力匹配导航的匹配效率改善研究.第一,为克服传统TERCOM算法逐点遍历搜索效率较低的缺点,提出新型分层邻域阈值搜索法.其原理如下:首先,利用4格网间隔数进行粗搜索匹配;其次,为提高初始匹配点的选取标准设置4mGal阈值(基准图上重力值与实测重力值之差),对选取的若干粗搜索行最佳匹配点周围24邻域点进行取舍并匹配比较;最后,获得搜索范围内最佳匹配点.第二,综合考虑了重力场标准差、峰度系数、坡度标准差、粗糙度、信息熵等重力场主要特征参数,将其作为适配区优劣的分析依据.第三,在适配性良好的区域内,在保证水下导航精度的前提下,基于分层邻域阈值搜索法,以本文参数设置为例,水下潜器重力匹配导航的匹配效率提高约14.14倍.

Improving the matching efficiency of underwater gravity matching navigation based on a new hierarchical neighborhood threshold method

This study focuses on improvement of underwater gravity matching navigation. Firstly, a new hierarchical neighborhood threshold method is proposed to overcome the shortcomings of the traditional TERCOM algorithm, such as the low search efficiency. Its principle is as follows:(1)A rough search match is performed using 4 grid intervals.(2)4 mGal threshold is set for improving the selection criteria of initial matching points (the difference between the gravity in a reference map and measured gravity), and 24 neighborhoods around the best matching points of rough search lines are selected and matched.(3)The best matching point in the search range is obtained. Secondly, we comprehensively consider the main characteristic parameters of the gravity map such as standard deviation, kurtosis coefficients, gradient, roughness and information entropy, and take them as a basis of navigability analysis. Finally, in the case of the parameter setting in this paper, the matching efficiency of underwater gravity matching navigation increases 14.14 times with accuracy being invariable using this new hierarchical neighborhood threshold method in a well-adjusted area.