RcppKalman: A C++ port usingRcppArmadillo of theEKF/UKF toolbox for Matlab
Why?
R has a number of existing Kalman filter packages which are all very noteworthy in their own right. A comparison was provided bythis JSS paper from 2011.
Yet I had a need for something both simple and fast at the C++ level.
TheEKF/UKF toolbox for Matlab proved to be a wonderful source of excellent code that was well documented (see [this 130 page pdf manual]http://becs.aalto.fi/en/research/bayes/ekfukf/documentation.pdf()), under a suitable license and covering both simple examples as well as promising extensions.
Demos
Static Sine Signal And Noisy Measurement
This example is not described in the pdf manual, but included as demokf_sine_demo.m within theEKF/UKF sources. A signal is provided via a sine wave plus random noise, and a linear Kalman Filter is used to smooth and filter the series. Our variantdemo/kf_sine_demo.R reproduces the demo via the following chart
Continuous Wiener-Process Acceleration
This demo is described in detail in Section 2.2.4 on pages 11 to 15 of theEKF/UKF Documentation; the animation is part of the corresponding Matlab code inkf_cwpa_demo.m. We show the two final charts which provide animations of the smoothing and filtering in our versiondemo/kf_cwpa_demo.R:
Status
Working, but still far from complete. We currently support two demo scripts based on linear smoothers and filters. Additional functions should get added over time.
Author
TheEKF/UKF Toolbox for Matlab was written by Simo Särkkä, Jouni Hartikainen, and Arno Solin.
Dirk Eddelbuettel is writing and maintaing this package by porting it to R and C++ viaRcpp and particularlyRcppArmadillo.
License
This package is released under GNU General Public License, Version 2 or later. EKF/UKF itself (which is included) is released under the GNU General Public License, Versions 2 and 3.
Initially created: Sun Apr 27 07:34:20 CDT 2014
Last modified: Wed Jun 17 18:01:10 CDT 2020