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海洋重力异常参考图特征及重力匹配辅助导航精度分析

Characteristics of Marine Gravity Anomaly Reference Maps and Accuracy Analysis of Gravity Matching-Aided Navigation.

作者信息

Wang Hubiao, Wu Lin, Chai Hua, Xiao Yaofei, Hsu Houtse, Wang Yong

机构信息

State Key Laboratory of Geodesy and Earth's Dynamics, Institute of Geodesy and Geophysics, Chinese Academy of Sciences, Wuhan 430077, China.

University of Chinese Academy of Sciences, Beijing 100049, China.

出版信息

Sensors (Basel). 2017 Aug 10;17(8):1851. doi: 10.3390/s17081851.

DOI:10.3390/s17081851
PMID:28796158
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5579750/
Abstract

The variation of a marine gravity anomaly reference map is one of the important factors that affect the location accuracy of INS/Gravity integrated navigation systems in underwater navigation. In this study, based on marine gravity anomaly reference maps, new characteristic parameters of the gravity anomaly were constructed. Those characteristic values were calculated for 13 zones (105°-145° E, 0°-40° N) in the Western Pacific area, and simulation experiments of gravity matching-aided navigation were run. The influence of gravity variations on the accuracy of gravity matching-aided navigation was analyzed, and location accuracy of gravity matching in different zones was determined. Studies indicate that the new parameters may better characterize the marine gravity anomaly. Given the precision of current gravimeters and the resolution and accuracy of reference maps, the location accuracy of gravity matching in China's Western Pacific area is ~1.0-4.0 nautical miles (n miles). In particular, accuracy in regions around the South China Sea and Sulu Sea was the highest, better than 1.5 n miles. The gravity characteristic parameters identified herein and characteristic values calculated in various zones provide a reference for the selection of navigation area and planning of sailing routes under conditions requiring certain navigational accuracy.

摘要

海洋重力异常参考图的变化是影响惯性导航系统/重力组合导航系统水下导航定位精度的重要因素之一。本研究基于海洋重力异常参考图,构建了重力异常的新特征参数。针对西太平洋地区13个区域(东经105° - 145°,北纬0° - 40°)计算了这些特征值,并进行了重力匹配辅助导航的模拟实验。分析了重力变化对重力匹配辅助导航精度的影响,确定了不同区域重力匹配的定位精度。研究表明,新参数可以更好地表征海洋重力异常。考虑到当前重力仪的精度以及参考图的分辨率和精度,中国西太平洋地区重力匹配的定位精度约为1.0 - 4.0海里(n mile)。特别是南海和苏禄海周边区域的精度最高,优于1.5 n mile。本文确定的重力特征参数以及各区域计算的特征值为在需要一定导航精度的条件下选择导航区域和规划航线提供了参考。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ebf/5579750/69c4e17a01d1/sensors-17-01851-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ebf/5579750/7959d718f97e/sensors-17-01851-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ebf/5579750/0fe4dd06beef/sensors-17-01851-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ebf/5579750/dd7472d64c41/sensors-17-01851-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ebf/5579750/57b226adabfc/sensors-17-01851-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ebf/5579750/fbf1ddb32b67/sensors-17-01851-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ebf/5579750/69c4e17a01d1/sensors-17-01851-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ebf/5579750/7959d718f97e/sensors-17-01851-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ebf/5579750/0fe4dd06beef/sensors-17-01851-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ebf/5579750/dd7472d64c41/sensors-17-01851-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ebf/5579750/57b226adabfc/sensors-17-01851-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ebf/5579750/fbf1ddb32b67/sensors-17-01851-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ebf/5579750/69c4e17a01d1/sensors-17-01851-g006.jpg

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本文引用的文献

1
Improved Feature Matching for Mobile Devices with IMU.用于配备惯性测量单元(IMU)的移动设备的改进特征匹配
Sensors (Basel). 2016 Aug 5;16(8):1243. doi: 10.3390/s16081243.
2
Performance Evaluation and Requirements Assessment for Gravity Gradient Referenced Navigation.重力梯度参考导航的性能评估与需求分析
Sensors (Basel). 2015 Jul 13;15(7):16833-47. doi: 10.3390/s150716833.
3
Marine geophysics. New global marine gravity model from CryoSat-2 and Jason-1 reveals buried tectonic structure.海洋地球物理学。CryoSat-2 和 Jason-1 揭示了新的全球海洋重力模型,揭示了埋藏的构造结构。
一种用于基于地图匹配的协同定位的可扩展框架。
Sensors (Basel). 2021 Sep 25;21(19):6400. doi: 10.3390/s21196400.
4
A New Scale Factor Adjustment Method for Magnetic Force Feedback Accelerometer.一种用于磁力反馈加速度计的新比例因子调整方法。
Sensors (Basel). 2017 Oct 27;17(11):2471. doi: 10.3390/s17112471.
Science. 2014 Oct 3;346(6205):65-7. doi: 10.1126/science.1258213. Epub 2014 Oct 2.
4
Improved artificial bee colony algorithm based gravity matching navigation method.基于改进人工蜂群算法的重力匹配导航方法
Sensors (Basel). 2014 Jul 18;14(7):12968-89. doi: 10.3390/s140712968.