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Analysis of the Dick Effect for AI-Based Dynamic Gravimeters.

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Τίτλος: Analysis of the Dick Effect for AI-Based Dynamic Gravimeters.
Συγγραφείς: Wang, Wen-Zhang1,2 (AUTHOR) wangwz@apm.ac.cn, Chen, Xi1,2,3 (AUTHOR) lijinting@apm.ac.cn, Li, Jin-Ting1,2,3 (AUTHOR), Zhang, Dan-Fang1,2,4 (AUTHOR), Xu, Wei-Hao1,2 (AUTHOR), Wei, Jia-Yi1,2 (AUTHOR), Zhong, Jia-Qi1,3,4 (AUTHOR), Tang, Biao1,4 (AUTHOR), Zhou, Lin1,4 (AUTHOR), Wang, Jin1,3,4 (AUTHOR), Zhan, Ming-Sheng1,3,4 (AUTHOR)
Πηγή: Sensors (14248220). Dec2025, Vol. 25 Issue 23, p7167. 14p.
Θεματικοί όροι: *Gravimetry, *Gravimeters (Geophysical instruments), *Gravimetric analysis, *Frequency-domain analysis, *Geophysics, *Noise measurement
Περίληψη: Atom interferometer (AI)-based dynamic gravimeters enable high-precision absolute gravity measurements, which are crucial for applications in geophysics, navigation, resource exploration, and metrology. Understanding their underlying mechanisms and minimizing measurement noise is essential for enhancing performance. This work investigates gravity-measurement noise in AI-based systems induced by the dead time of the classical accelerometer. Using actual dynamic gravity-measurement data, we demonstrate that a dead time of 0.12 s introduces significant gravity-measurement noise, reaching 8 mGal. To elucidate the mechanism of this noise, we derive a frequency-domain formula, identifying high-frequency aliasing as its source. Analysis of the derived expressions indicates that reducing the dead-time duration and suppressing the acceleration's high-frequency noise are effective strategies for mitigating this noise. This work provides significant insights into noise analysis and the future design of AI-based dynamic gravimeters. [ABSTRACT FROM AUTHOR]
Βάση Δεδομένων: Academic Search Index
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  Data: Analysis of the Dick Effect for AI-Based Dynamic Gravimeters.
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  Data: Atom interferometer (AI)-based dynamic gravimeters enable high-precision absolute gravity measurements, which are crucial for applications in geophysics, navigation, resource exploration, and metrology. Understanding their underlying mechanisms and minimizing measurement noise is essential for enhancing performance. This work investigates gravity-measurement noise in AI-based systems induced by the dead time of the classical accelerometer. Using actual dynamic gravity-measurement data, we demonstrate that a dead time of 0.12 s introduces significant gravity-measurement noise, reaching 8 mGal. To elucidate the mechanism of this noise, we derive a frequency-domain formula, identifying high-frequency aliasing as its source. Analysis of the derived expressions indicates that reducing the dead-time duration and suppressing the acceleration's high-frequency noise are effective strategies for mitigating this noise. This work provides significant insights into noise analysis and the future design of AI-based dynamic gravimeters. [ABSTRACT FROM AUTHOR]
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              M: 12
              Text: Dec2025
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