Acceleration estimation using a single GPS receiver for airborne scalar gravimetry. Issue 10 (15th November 2017)

• Record Type: Journal Article
• Authors: Zhang, Xiaohong; Zheng, Kai; Lu, Cuixian; Wan, Jiakuan; Liu, Zhanke; Ren, Xiaodong
• Is Part Of: Advances in space research. Volume 60:Issue 10(2017)
• Page Start: 2277
• Page End: 2288
• Publication Date: 2017-11-15
• Subjects: GPS -- Single receiver -- Kin-VADASE -- Airborne scalar gravimetry -- Acceleration estimation; Space sciences -- Periodicals; Astronautics -- Periodicals; Geophysics -- Periodicals; 500.505
• DOI: 10.1016/j.asr.2017.08.038
• Languages: English
• ISSNs: 0273-1177

Abstract

Abstract: Kinematic acceleration estimated using the global positioning system (GPS) is significant for airborne scalar gravimetry. As the conventional approach based on the differential global positioning system (DGPS) presents several drawbacks, including additional cost or the impracticality of setting up nearby base stations in challenging environments, we introduce an alternative approach, Modified Kin-VADASE (MKin-VADASE), based on a modified Kin-VADASE approach without the requirement to have ground-base stations. In this approach, the aircraft velocities are first estimated with the modified Kin-VADASE. Then the accelerations are obtained from velocity estimates using the Taylor approximation differentiator. The impact of carrier-phase measurement noise and satellite ephemeris errors on acceleration estimates are investigated carefully in the frequency domain with the Fast Fourier Transform Algorithm (FFT). The results show that the satellite clock products have a significant impact on the acceleration estimates. Then, the performance of MKin-VADASE, PPP, and DGPS are validated using flight tests carried out in Shanxi Province, China. The accelerations are estimated using the three approaches, then used to calculate the gravity disturbances. Finally, the analysis of crossover difference and the terrestrial gravity data are used to evaluate the accuracy of gravity disturbance estimates. The results show that the performances of MKin-VADASE, PPP and DGPS are comparable, but the computational complexity of MKin-VADASE is greatly reduced with regard to PPP and DGPS. For the results of the three approaches, the RMS of crossover differences of gravity disturbance estimates is approximately 1–1.5 mGal at a spatial resolution of 3.5 km (half wavelength) after crossover adjustment, and the accuracy is approximately 3–4 mGal with respect to terrestrial gravity data.