Abstract
Analysis of two accelerometers’ observation data using maximum relative entropy principles by satisfying both time series and model constraints is presented. Convex optimization principles are used to find the maximum entropy priori probability function. And the likelihood is inferred simultaneously during a priori calculations. Performance is taken into account when developing real time analysis with iteration free optimization. As a result zero bias estimation function is derived for accelerometers’ axis and it confirms the value which is manually found when observing Earth’s gravity under static conditions, i.e. when accelerometer is not moving. Ill. 1, bibl. 5 (in English; abstracts in English, Russian and Lithuanian).
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