Matching area selection for arctic gravity matching navigation based on adaptive all‐field extended extremum algorithm

Author:

Xi Menghan12ORCID,Wu Lin12,Li Qianqian12,Mao Guocheng13,Wu Pengfei12,Ji Bing4,Bao Lifeng12,Wang Yong12

Affiliation:

1. State Key Laboratory of Geodesy and Earth's Dynamics Innovation Academy for Precision Measurement Science and Technology Chinese Academy of Sciences Wuhan China

2. University of Chinese Academy of Sciences Beijing China

3. School of Geography and Information Engineering China University of Geosciences Wuhan China

4. Department of Electrical Engineering Naval University of Engineering Wuhan China

Abstract

AbstractSuitable and effective matching area selection is crucial for gravity matching‐aided navigation. In this paper, an all‐field extended extremum algorithm based on an adaptive threshold (AT‐AEE) is proposed for matching area selection in the Arctic Sea. The gradient data is obtained by using the convolution of gravity reference graph data and all‐field extended extremum parameters. Then, the adaptive threshold method was employed to determine the optimal gradient threshold based on gravity anomaly data across various test areas. Data points with gradients exceeding the specified threshold are identified as local candidate points for matching areas. The test areas containing a certain proportion of local candidate points are designated as the suitable matching areas. Nine test areas in the Arctic Sea with different gravity change characteristics were chosen for simulation experiments to verify the performance of the proposed algorithm. Simulation experiments showed that superior navigation positioning results could be obtained in the matching areas selected by the AT‐AEE algorithm. Compared to traditional algorithm, the matching areas derived from the AT‐AEE algorithm performed with a better consistency in the gravity matching navigation results. In suitable matching areas with the proportion of local candidate points reaching 70%, the average positioning errors could be reduced to less than 1.5 n miles.

Funder

National Natural Science Foundation of China

Publisher

Institution of Engineering and Technology (IET)

Reference18 articles.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3