Several Kinematic Data Processing Methods for Time-correlated Observations

doi:10.11947/j.AGCS.2018.20180192

Abstract

Abstract: Time correlations always exist in modern geodetic data, and ignoring these time correlations will affect the precision and reliability of solutions. In this paper, several kinematic data processing methods for time-correlated observations are studied. Firstly, the method for processing the time-correlated observations is expanded and unified. Based on the theory of maximum a posteriori estimation, the third idea is proposed. Two types of situations with and without common parameters are both investigated by using the decorrelation transformation, differential transformation and maximum a posteriori estimation solutions. Besides, the characteristics and equivalence of above three methods are studied. Secondly, in order to balance the computational efficiency in real applications and meantime effectively capture the time correlations, the corresponding reduced forms based on the autocorrelation function are deduced. Finally, with GPS real data, the correctness and practicability of derived formulae are evaluated.

Key words: time correlation, kinematic solution, decorrelation transformation, differential transformation, maximum a posteriori estimation

CLC Number:

P207

LI Bofeng, ZHANG Zhetao. Several Kinematic Data Processing Methods for Time-correlated Observations[J]. Acta Geodaetica et Cartographica Sinica, 2018, 47(12): 1563-1570.

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