发表机构
Istituto Nazionale di Geofisica e Vulcanologia (INGV); Istituto di Astrofisica e Planetologia Spaziali (IAPS), Istituto Nazionale di Astrofisica (INAF)（意大利地球物理和火山学研究所; 国家天体物理学研究所空间天文和行星科学研究所）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究提出一种基于多传感器系统、监督机器学习和专用实验室训练平台的通用框架，用于补偿航空与海洋重力测量中的干扰，并针对应用难题提出了专门解决方案。
AI 中文摘要
在复杂作业环境中运行的高精度测量系统，如航空和海洋重力测量，会受到温度变化、惯性加速度、平台旋转等相互作用的外部影响（干扰）的严重影响。本研究旨在开发并验证一种通用方法，以补偿超出传统方法极限的此类干扰。我们提出了一个基于三大支柱的通用框架：多传感器系统、监督机器学习以及专用实验室训练平台。该测量技术通过两个与航空和海洋重力测量相关的实验案例研究进行了验证：（i）高灵敏度三轴加速度计中的温度和热梯度抑制，（ii）用于垂直加速度估计的俯仰和横滚抑制。实验表明，尽管该通用框架提供了有用的指导方针，但其在航空和海洋重力测量中的应用具有挑战性且并非直截了当，需要开发专用且创新的实验解决方案。这种困难源于被测量对象——重力的特殊性质，其无法在受控条件下轻易改变。在本研究中，我们提出了一种专门的方法来应对这些挑战。
英文摘要
High-accuracy measurement systems operating in complex operational environments, such as airborne and seaborne gravimetry, are severely affected by interacting external influences (disturbances) including temperature variations, inertial accelerations, and platform rotations. This work aims to develop and prove a general method for compensating such disturbances beyond the limits of conventional approaches. We present a general framework based on three pillars: a multi-sensor system, supervised machine learning, and a dedicated laboratory -training platform-. This measurement technique was investigated through two experimental case studies relevant to airborne and seaborne gravimetry: (i) temperature and thermal-gradient rejection in a high-sensitivity tri-axial accelerometer, and (ii) pitch and roll rejection for vertical acceleration estimation. The experiments highlighted that, although the general framework provides a useful guideline, its application to airborne and seaborne gravimetry is challenging and not straightforward, requiring the development of dedicated and innovative experimental solutions. This difficulty arises from the specific nature of the measurand-gravity-which cannot be easily varied under controlled conditions. In this work, we present a dedicated approach to addressing these challenges.
Journal refPublished 25 August 2026 Copyright 2026 The Author(s). Published by IOP Publishing Ltd Measurement Science and Technology, Volume 37, Number 34 Citation Lorenzo Iafolla et al 2026 Meas. Sci. Technol. 37 346002
