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Scalar Airborne Gravimetry Using Low Pass Filter with Different Windows
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Ahmad Ghonchi   , Yazdan Amerian * , Mohammad Shakibay Senobari |
| K.N.Toosi University of Technology |
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Abstract: (3688 Views) |
| In airborne gravimetry, the integration of Global Positioning System (GPS) and Inertial Navigation System (INS) is used for Earth gravity field recovery. GPS position is noisy and the GPS acceleration which is the second derivate of GPS position will be noisy too and noise amount of GPS acceleration exacerbates due to the computational errors of differentiation process. The INS acceleration also has high amount of noise. Digital low-pass differentiator filter is used to calculate the GPS acceleration from GPS position and reduce the GPS acceleration noise as much as possible. Then digital low-pass filter with different windows have been used to smooth and reduce noise of the GPS and INS acceleration. Gravity is determined by differentiating the smoothed GPS and INS acceleration. Gravity disturbance is computed as the difference of computed gravity and normal gravity. The INS accelerometer and gyroscope errors includes bias, scale factor and random noise affect the accuracy of calculated gravity disturbance. The gravity disturbance value as observations and the error dynamic equations of the INS are applied in a Kalman filter for INS errors estimation. This paper has shown that using low-pass filters with product of Hanning and Blackman window, Blackman window and Kaiser window with appropriate parameter as a smoothing method will be rulted in gravity with the accuracy about 1 mGal which is comparable with B-spline smoothing method which has been applied to this data before. Comparing low-pass filter and B-spline smoothing methods, simplicity and less time consuming can be mentioned as low-pass filter advantages. Also the degree of smoothing can be controlled using filter order. |
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| Keywords: GPS, INS, Digital Low Pass Filter, Smoothing, Gravity |
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Full-Text [PDF 1796 kb]
(1558 Downloads)
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Type of Study: Research |
Subject:
Geodesy
Received: 2017/08/7 | Accepted: 2017/09/18 | Published: 2018/03/19
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