https://github.com/gabrielenava/eigenukf
Implementation of the Unscented Kalman Filter (UKF) in C++ using Eigen.
https://github.com/gabrielenava/eigenukf
cpp eigen estimation unscented-kalman-filter
Last synced: 3 months ago
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Implementation of the Unscented Kalman Filter (UKF) in C++ using Eigen.
- Host: GitHub
- URL: https://github.com/gabrielenava/eigenukf
- Owner: gabrielenava
- License: bsd-3-clause
- Created: 2023-10-28T12:26:57.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-12-27T20:38:11.000Z (10 months ago)
- Last Synced: 2025-06-22T12:13:37.797Z (4 months ago)
- Topics: cpp, eigen, estimation, unscented-kalman-filter
- Language: C++
- Homepage:
- Size: 408 KB
- Stars: 3
- Watchers: 2
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# EigenUKF
[](https://github.com/gabrielenava/Eigen_UKF/actions/workflows/ci_ukf.yml)
A C++ implementation of the Unscented Kalman Filter (UKF) using Eigen. The UKF uses a deterministic sampling technique known as the Unscented Transformation to calculate statistics around the mean. This technique does not require differentiability of the models.
See also https://groups.seas.harvard.edu/courses/cs281/papers/unscented.pdf for more details.
For the implementation I took inspiration from https://github.com/CoffeeKumazaki/kalman_filters.
## Installation and usage
**Tested only on Ubuntu 20.04 LTS**
### Dependencies
- [Eigen3](https://eigen.tuxfamily.org/index.php?title=Main_Page) library.
### Compilation
Clone the repo on your PC. Then, enter the folder where you downloaded the repo, open a terminal and run:
```
mkdir build && cd build
cmake .. -DCMAKE_INSTALL_PREFIX="/path/to/desired/install/dir"
make install
```
The UKF library will be available in the `install/lib` folder. The library is composed of two classes:
- [UnscentedKF](lib/src/UnscentedKF.cpp): implementation of the Unscented Kalman Filter in c++. Provides methods to set up a routine for estimation/filtering of user-defined quantities via UKF. Works alongside with the UKFModel class which provides the prediction and observation models.
- [UKFModel](lib/src/UKFModel.cpp): defines the prediction and observation models for the UnscentedKF class. This is an abstract class: the user must create his own child class derived from UKFModel, and implement with it the prediction and observation models for his specific problem.
### Example
An example of usage of the library is available in the [example](example) folder. The filter is used to estimate the thrust provided by a jet engine and its rate of change, given the measured thrust data.
### Test
A simple test to verify library integrity is provided in the [test](test) folder. The test uses [Catch2](https://github.com/catchorg/Catch2.git) library and can be run with the `ctest` command from the `build` directory.
## Maintainer
Gabriele Nava, @gabrielenava