Abstract
Surveying the Earth’s gravity field refers to an important domain of Geodesy, involving deep connections with Earth Sciences and Geo-information. Airborne gravimetry is an effective tool for collecting gravity data with mGal accuracy and a spatial resolution of several kilometers. The main obstacle of airborne gravimetry is extracting gravity disturbance from the extremely low signal to noise ratio measuring data. In general, the power of noise concentrates on the higher frequency of measuring data, and a low pass filter can be used to eliminate it. However, the noise could distribute in a broad range of frequency while low pass filter cannot deal with it in pass band of the low pass filter. In order to improve the accuracy of the airborne gravimetry, Empirical Mode Decomposition (EMD) is employed to denoise the measuring data of two primary repeated flights of the strapdown airborne gravimetry system SGA-WZ carried out in Greenland. Comparing to the solutions of using finite impulse response filter (FIR), the new results are improved by 40% and 10% of root mean square (RMS) of internal consistency and external accuracy, respectively.
Highlights
The Earth’s gravity field, which is responsible of the structure and shape of the earth, is of primary importance for much Earth science based research and applications as well as for practical applications in geo-information
According to Newton’s second law of motion and gravity disturbance’s definition [10], in an inertial frame, the gravity disturbance vector can be reckoned directly from the total acceleration fi sensed by accelerometers of the gravimeter, the kinematic acceleration ri of the aircraft and the normal gravity field Ύ
Empirical Mode Decomposition (EMD), which has the potential of estimating the trend of data is a new technique of decomposing a given signal into a set of limited Intrinsic Mode Functions (IMFs) [21]
Summary
The Earth’s gravity field, which is responsible of the structure and shape of the earth, is of primary importance for much Earth science based research and applications as well as for practical applications in geo-information. Infinite impulse response (IIR) filters are the two widely used low-pass filters in airborne gravity data processing. The effects of attitude errors and aircraft dynamics often evoke observation errors at lower frequency; low-pass filters will not work except if the length of the filter is no less than the period of phugoid motion [19,20] Even though both noise and signals are eliminated in the lower wavelength, some noise still exists in the pass-band which will contaminate the accuracy of the result [5]. The empirical mode decomposition (EMD) proposed in 1998 by Huang of NASA has the potential of estimating and analyzing the trend of the data [21] It is a time-frequency analysis method of processing a nonlinear non-stationary signal, which has been applied in the fields of nonlinear system. After descripting and analyzing the data obtained from the primary repeated flight profiles of SGA-WZ, EMD is employed to estimate gravity disturbances from the raw data
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