Licence minimal R version

🛰️ navigation Overview

The navigation R package allows to analyze the impact of sensor error modeling on performance of integrated navigation (sensor fusion) based on IMU, GPS (generally speaking, GNSS), and barometer data. The package allows for one of the two major tasks:

Caution A flat non-rotating Earth model is assumed throughout the package. We consider this not to be of major impact on sensor model evaluation, as the main contributor there are match/mismatch between the additive sensor errors and the provided error models to the navigation filter. For absolute navigation results though, is long distances and high speeds are involved, such simplifications start to have measurable impact on results. Also, attitude parameterization is done via Euler angles at the moment, bringing their interinsic limitations, such as the singularity at pitch \(=\pm \pi/2\). This limitation may be resolved in future using other attitude parameterizations such as quaternions.

Installation Instructions

The navigation package is currently only available on GitHub.

Furthermore, the package is currently in an early development phase. Some functions are stable and some are still in development. Moreover, the GitHub version is subject to modifications/updates which may lead to installation problems or broken functions.

You can install the latest version of the navigation package with:

# Install devtools package if not already installed
if (!require("devtools")) {

# Install package from GitHub

External R libraries

The navigation package relies on a limited number of external libraries, but notably on Rcpp and RcppArmadillo which require a C++ compiler for installation, such as for example gcc.


Find detailled usage instructions, examples and the user’s manual at the package website.


This source code is released under is the GNU AFFERO GENERAL PUBLIC LICENSE (AGPL) v3.0.


D. A. Cucci, L. Voirol, M. Khaghani and S. Guerrier, “On Performance Evaluation of Inertial Navigation Systems: the Case of Stochastic Calibration,” in IEEE Transactions on Instrumentation and Measurement, doi: 10.1109/TIM.2023.3267360.