摘要
针对平台式重力仪大机动状态后测量能力恢复慢的问题,提出一种基于BP神经网络的重力仪稳定平台快速调平修正技术。首先,针对动态重力测量在测量平台大机动状态后调平能力不足的问题,研究了基于BP神经网络的平台姿态高效、准确解算方法;其次,利用惯性元件和卫星导航系统(GNSS)的信息优化BP神经网络,形成不同条件的平台姿态提取优化模型;最后,利用模拟仿真实验和实际机载动态重力测量数据验证所提方法的有效性和准确性。实验结果表明在大机动的动态条件下采用所提方法可以扶正重力仪稳定平台,将机动后重力仪稳定平台稳定时间缩短83.3%以上,提升动态重力测量效率。
Aiming at the problem of slow recovery of measuring ability after large maneuvering state of platform-type gravimeter,a control technology based on the BP neural network is proposed to stabilize the platform to quickly level and correct the platform.First of all,in response to the low levelling ability of the platform in large maneuvering state during dynamic gravity measurement,an efficient and accurate solution method based on BP neural network is proposed.Secondly,the BP neural network is optimized by using the information of inertial elements and global navigation satellite system(GNSS),and optimal models of platform attitude extraction under different conditions are formed.Finally,simulation experiments and actual airborne dynamic gravity measurement data are used to verify the effectiveness and accuracy of the proposed method.The experimental results show that the proposed method can be used to upright the gravimeter platform under the dynamic conditions of large maneuvering.The stability time of the platform can be decreased by more than 83.3%,and the efficiency of dynamic gravity measurement can be improved.
作者
杨晔
董光泰
高巍
张子山
YANG Ye;DONG Guangtai;GAO Wei;ZHANG Zishan(Tianjin Institute of Navigational Instruments,Tianjin 300131,China;Laboratory of Science and Technology on Marine Navigation and Control,China State ShipbuildingCorporation,Tianjin 300131,China)
出处
《中国惯性技术学报》
EI
CSCD
北大核心
2024年第5期457-462,共6页
Journal of Chinese Inertial Technology
基金
国家重点研发计划课题(2021YFHB3900203)。
关键词
动态重力测量
平台式重力仪
BP神经网络
平台快速修正
dynamic gravity measurement
platform-type gravimeter
BP neural network
platform fast correction
