Moving Base Gravity Gradiometer Survey (GGSS) Program

Online error compensation of moving-base rotating accelerometer gravity gradiometer

Review of Scientific Instruments ◽

10.1063/1.5093078 ◽

2019 ◽

Vol 90 (7) ◽

pp. 074501 ◽

Cited By ~ 1

Author(s):

Mingbiao Yu ◽

Tijing Cai

Keyword(s):

Error Compensation ◽

Gravity Gradiometer ◽

Moving Base

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Gravity gradiometer survey errors

Geophysics ◽

10.1190/1.1442414 ◽

1988 ◽

Vol 53 (10) ◽

pp. 1355-1361 ◽

Cited By ~ 11

Author(s):

Steven J. Brzezowski ◽

Warren G. Heller

Keyword(s):

Total Error ◽

Estimation Algorithm ◽

Error Variance ◽

Downward Continuation ◽

Gravity Gradiometer ◽

Limited Data ◽

Gravity Disturbance ◽

System Noise ◽

Disturbance Vector ◽

Moving Base

Gradiometer system noise, sampling effects, downward continuation, and limited data extent are the important contributors to moving‐base gravity gradiometer survey error. We apply a two‐dimensional frequency‐domain approach in simulations of several sets of airborne survey conditions to assess the significance of the first two sources. A special error allocation technique is used to account for the downward continuation and limited extent effects. These two sources cannot be modeled adequately as measurement noise in a linear error estimation algorithm. For a typical characterization of the Earth’s gravity field, our modeling indicates that limited data extent generally contributes about one‐half of the total error variance associated with recovery of the gravity disturbance vector at the Earth’s surface; gradiometer system noise typically contributes about one‐third. However, sampling effects are also very important (and are controlled through the survey track spacing). A 5 km track spacing provides a reasonable tradeoff between survey cost and errors due to track spacing. Furthermore, our results indicate that a moving‐base gravity gradiometer system can recover each component of the gravity disturbance vector with an rms accuracy better than 1.0 mGal.

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