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The identification and selection of a small set of models that are able to well describe and predict the error signals coming from IMU sensors is of utmost importance to improve the navigation precision of these devices. For this reason, in this paper we p ...
A new open-source software platform that, among others, allows to select models for inertial sensor stochastic calibration is presented in this paper. This platform consists in a package included in the statistical software R. The identification of stochas ...
IEEE2015
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The integration of observations issued from a satellite-based system (GNSS) with an inertial navigation system (INS) is usually performed through a Bayesian filter such as the extended Kalman filter (EKF). The task of designing the navigation EKF is strong ...
Institute of Electrical and Electronics Engineers2014
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This article presents a new estimation method for the parameters of a time series model. We consider here composite Gaussian processes that are the sum of independent Gaussian processes which, in turn, explain an important aspect of the time series, as is ...
Amer Statistical Assoc2013
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Stochastic modeling is a challenging task for low- cost inertial sensors whose errors can have complex spectral structures. This makes the tuning process of the INS/GNSS Kalman filter often sensitive and difficult. We are currently investigating two approa ...
Inst Navigation2011
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We present an algorithm for determining the nature of stochastic processes together with its parameters based on the analysis of time series of inertial errors. The algorithm is suitable mainly (but not only) for situations when several stochastic processe ...
2013
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This research presents methods for detecting and isolating faults in multiple micro-electro-mechanical system inertial measurement unit (MEMS-IMU) configurations. First, geometric configurations with n sensor triads are investigated. It is proved that the ...
Institute of Electrical and Electronics Engineers2012
We present an algorithm for determining the nature of stochastic processes and their parameters based on the analysis of time series of inertial errors. The algorithm is suitable mainly (but not only) for situations where several stochastic processes are s ...
Proposed 50 years ago for studying stability of oscillators, Allan Variance (AV) was accepted by IEEE as a standard for characterizing behavior of sensors. However, the inverse mapping, i.e. the estimation of noise-parameters from Allan Variance is less st ...
Modeling and estimation of gyroscope and accelerometer errors is generally a very challenging task, especially for low-cost inertial MEMS sensors whose systematic errors have complex spectral structures. Consequently, identifying correct error-state parame ...