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An Algorithm for Strapdown Airborne Gravity Disturbance Vector Measurement Based on High-Precision Navigation and EGM2008
by
Fang, Ke
, Cai, Tijing
in
Accelerometers
/ Accuracy
/ Aircraft
/ Algebra
/ Algorithms
/ Bias
/ EGM2008 model
/ error separation and compensation
/ Global positioning systems
/ GPS
/ Gravity
/ gravity disturbance vector measurement
/ Lie groups
/ Measurement techniques
/ Propagation
/ strapdown navigation algorithm
/ Trends
2024
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An Algorithm for Strapdown Airborne Gravity Disturbance Vector Measurement Based on High-Precision Navigation and EGM2008
by
Fang, Ke
, Cai, Tijing
in
Accelerometers
/ Accuracy
/ Aircraft
/ Algebra
/ Algorithms
/ Bias
/ EGM2008 model
/ error separation and compensation
/ Global positioning systems
/ GPS
/ Gravity
/ gravity disturbance vector measurement
/ Lie groups
/ Measurement techniques
/ Propagation
/ strapdown navigation algorithm
/ Trends
2024
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While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
An Algorithm for Strapdown Airborne Gravity Disturbance Vector Measurement Based on High-Precision Navigation and EGM2008
by
Fang, Ke
, Cai, Tijing
in
Accelerometers
/ Accuracy
/ Aircraft
/ Algebra
/ Algorithms
/ Bias
/ EGM2008 model
/ error separation and compensation
/ Global positioning systems
/ GPS
/ Gravity
/ gravity disturbance vector measurement
/ Lie groups
/ Measurement techniques
/ Propagation
/ strapdown navigation algorithm
/ Trends
2024
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An Algorithm for Strapdown Airborne Gravity Disturbance Vector Measurement Based on High-Precision Navigation and EGM2008
Journal Article
An Algorithm for Strapdown Airborne Gravity Disturbance Vector Measurement Based on High-Precision Navigation and EGM2008
2024
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Overview
Attitude errors, accelerometer bias, the gravity disturbance vector, and their coupling are the primary factors obstructing strapdown airborne vector gravimetry. This paper takes the geocentric inertial frame as a reference and solves the kinematic equations of its motion and its errors of the body frame and local geographic frame in the Lie group, respectively; the attitude accuracy is improved through a high-precision navigation algorithm. The constant accelerometer bias is estimated through Kalman filtering and is deducted from the accelerometer output to eliminate its influence. Based on the EGM2008 model, the low-frequency components of the gravity disturbance vector are corrected. The gravity disturbance vectors after model data fusion were low-pass filtered to obtain the ultimate results. This method was applied to flight experimental data in the South China Sea, and a gravity anomaly accuracy of better than 0.5 mGal, a northward gravity disturbance accuracy of 0.85 mGal, and an eastward gravity disturbance accuracy of 4.0 mGal were obtained, with a spatial resolution of approximately 4.8 km.
Publisher
MDPI AG,MDPI
Subject
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