Mechanics

Adaptive filtering of airborne gravimetry data using hidden Markov models

Yu. V. Bolotin, D. R. Doroshin

Lomonosov Moscow State University, Faculty of Mechanics and Mathematics

Abstract: The paper studies the adaptive filtering of airborne gravimetry data on a survey line, where the inhomogeneous gravity in time is induced by the unknown structure of the Earth's core, topography, etc. Gravity is modeled by a hidden Markov chain with a finite number of states, each state corresponds to a certain type of the gravity profile. The problem under study is solved with consideration of the type of noises of the global positioning system.

Key words: gravimetry, airborne gravimetry, adaptive filtering, hidden Markov models, moving average.

UDC: 531.38

Received: 18.06.2010

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