• ISSN 2097-1893
    • CN 10-1855/P

    新一代卫星重力梯度仪的多源误差特征分析与精度评估

    Multi-source error characterization and performance assessment of next-generation satellite gravity gradiometers for Earth gravity field recovery

    • 摘要: GOCE作为首颗专用重力梯度探测卫星,显著提升了全球重力场模型的精度和空间分辨率. 然而,基于静电悬浮加速度计的重力梯度仪易受低频热漂移和尺度因子不稳定等因素影响,其测量性能进一步提升受到限制,进而制约了重力场恢复精度的提高和重力梯度观测应用的发展. 近年来,冷原子干涉加速度计、混合加速度计(HyACC)以及MicroSTAR多轴加速度计等新一代传感器快速发展,为未来高精度卫星重力梯度任务提供了新的技术途径. 然而,现有研究多针对单一传感器或特定误差源开展分析,多源误差综合影响及不同重力梯度仪配置之间的性能差异仍缺乏系统评估. 为此,本文构建了一套统一的闭环数值模拟框架,系统分析多源误差对新一代卫星重力梯度仪地球重力场恢复性能的影响,并对不同类型重力梯度仪配置开展综合性能评估. 结果表明,HyACC4配置表现出最佳综合性能,在200阶时累积大地水准面误差较GOCE降低63.44%;冷原子重力梯度仪和六分量MicroSTAR重力梯度仪对应误差分别降低57.24%和51.69%,且六分量MicroSTAR配置相比对应的三分量配置具有更优的恢复能力. 进一步分析发现,新一代重力梯度仪的性能不仅受加速度计噪声水平影响,还与多源误差的频率特性及其传播过程密切相关. 研究揭示了不同类型重力梯度仪的误差特征及性能差异,为未来卫星重力任务中的载荷选型、系统优化和任务设计提供了理论依据和定量参考.

       

      Abstract: The GOCE mission, as the first dedicated gravity gradiometry satellite, has significantly improved the accuracy and spatial resolution of global gravity field models. However, the performance of its electrostatic accelerometer-based gradiometer is limited by low-frequency thermal drift and scale-factor instability, which restrict further improvements in gravity field recovery and the broader application of gravity gradiometry observations. Recent advances in next-generation sensors, including cold atom interferometry (CAI) accelerometers, hybrid accelerometers (HyACC), and MicroSTAR multi-axis accelerometers, provide new opportunities for enhancing future satellite gravity gradiometry missions. Although previous simulation studies have demonstrated the potential of these technologies, the comprehensive effects of multi-source errors and the relative performance of different gradiometer configurations have not yet been fully quantified. This study establishes a unified closed-loop numerical simulation framework to characterize multi-source error impacts and evaluate the gravity field recovery capability of next-generation gravity gradiometers. The analysis reveals that the HyACC4 configuration achieves the best overall performance, reducing the cumulative geoid error at degree 200 by 63.44% relative to GOCE. The CAI gradiometer and six-component MicroSTAR configuration achieve corresponding reductions of 57.24% and 51.69%, respectively, with the six-component MicroSTAR configuration outperforming the corresponding three-component configuration. The results further demonstrate that the performance of next-generation gradiometers is determined not only by accelerometer noise characteristics but also by the frequency-dependent propagation of multiple error sources. These findings provide a systematic understanding of the error characteristics and performance capabilities of next-generation gravity gradiometers, offering quantitative guidance for payload selection, configuration optimization, and future satellite gravity mission design.

       

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