Unscented Kalman filter library.

ukf/include contains the header files, divided into the following:

• dynamics.h: Dynamics models. A simple centripetal model and a fixed-wing aerodynamic model are provided.
• integrator.h: Integration routines. A 4th-order Runge-Kutta, 2nd-order Heun method, or 1st-order Euler method can be selected.
• sensors.h: Defines the SensorModel interface and a model of the I/O board's sensors.
• state.h: Declares the State type, a 25-dimensional column vector used to represent the state of the Kalman filter. Individual components of the State type can be accessed using the accessor methods provided.
• types.h: Defines the real_t type (either a single- or double-precision floating-point, depending on the precision selected in config.h), and a few required constants.
• ukf.h: Defines the interface to the Unscented Kalman Filter, along with sigma point scaling constants, MRP parameters and sigma point weights.

ukf/src contains source files, hopefully divided into logical components:

• dynamics.cpp: Functions relating a state vector to the linear and angular acceleration.
• sensors.cpp: The I/O board sensor model, including measurement prediction and mean finding functions.
• state.cpp: Kinematic state transition function.
• ukf.cpp: The Kalman filter proper.
• ukf-estimates.cpp: Kalman filter estimation functions, broken out into a separate file to work around issues in the Texas Instruments CCS compiler.

ukf/test contains unit tests, built using the googletest framework.

ukf/c is the source to libcukf, a C interface to the C++ UKF static library.

ukf/python contains a ctypes-based Python wrapper for libcukf.

ukf/ccs-c66x contains a project for Texas Instruments Code Composer Studio 5, targeting the Keystone DSP platform (C66x cores). This project uses the libcukf API, but implements the functions directly in C66-optimized C rather than using the C++/Eigen implementation from libcukf.

src/config.h is currently used for configuration. The parameters which can be configured here are as follows:

• The precision (single or double) of the floating-point values used by the library;
• The integration method used (RK4, Heun or Euler).

The default configuration is double-precision and RK4; other configurations are functional but have not been tested using live data.

Requires cmake version 2.8.7 or higher.

Create a build directory outside the source tree, then use cmake to generate the makefile.

mkdir ukf_build
cd ukf_build
cmake /path/to/ukf

Now, build the library using the make command. An appropriate version of Eigen will be downloaded automatically.

To build the dynamic library, run make cukf. A dynamic library appropriate for the host platform should be built.

The googletest library is used for unit testing. To build the unit tests, use make unittest. The unit tests can then be executed by running test/unittest in the build directory.

Requires cmake version 2.8.7 or higher.

Run python setup.py install to build the C shared library and install the Python interface (the ukf module) in your site-packages directory.

Alternatively, just run pip install https://github.com/sfwa/ukf/archive/master.zip#egg=ukf-1.0.0 to download and install.

Import the root directory of this project (ukf) into your workspace. CCS should search all contained files, and find a project in ccs-c66x. Complete the import, and build.