Adaptive filtering of airborne gravimetry data using hidden Markov models

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.