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IMU Error State Modeling for State Estimation and Sensor Calibration: A Tutorial

  • Author(s): Farrell, Jay A
  • Silva, Felipe O.
  • Rahman, Farzana
  • Wendel, Jan
  • et al.
Abstract

This article is a tutorial describing the process and issues related to developing a state-space model for the stochastic errors affecting an Inertial Measurement Unit (IMU). The starting point is the instrument error characterization data sheet provided by the manufacturer, which is typically either an Allan Variance graph or the parameters extracted from that graph. Along with this tutorial, supplementary software is available for open source distribution that calculates and plots the Allan Variance for a given set of data; extracts optimal parameters (e.g., $Q_N$, $Q_B$, $Q_K$, and $T_B$) from Allan Variance data for a given model structure; and, computes and simulates of the discrete-time equivalent model.

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