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

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.