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ivo-georgiev/ukfLib

version 1.2.0.0 (7.37 MB) by Ivo Georgiev
Unscented Kalman filter C library, s-function and configuration GUI tool

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Updated 16 Jan 2018

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Unscented Kalman filter C library
What is included:
- mtxLib.c, mtxLib.h : Library with some basic matrix functions required for UKF implementation(cholesky decomposition, matrix inversion, matrix operation, i.e).
- ukfLib.c, ukfLib.h : Unscented Kalman filter implementation.
- ukfCfg.c,ukfCfg.h : These files contain UKF matrix and mathematical state space models/equation(state and measurement equations).They are specific for every different nonlinear filtering problem. In current project these files adress the issue from Matthew B Rhudy tutorial(Understanding Nonlinear Kalman Filters, Part II:An Implementation Guide): https://web.statler.wvu.e/~irl/IRL_WVU_Online_UKF_Implementation_V1.0_06_28_2013.pdf
-ukfCfg1.c,ukfCfg1.h : This configuration is used for estimation of angle and angular speed of free pendulum.
-test2.c : file is used for both simulation and unit testing. It also show how filter should be initialized and used in practice.
-Matlab model(R2013b) with s-fun for simulation and verification of each configuration(cfg1,cfg2,..,cfgN) in Simulink enviroment.This model use files listed above to build and simulate s-function.
-Matlab GUI tool for easy filter configuration and automatic file generation(ukfCfgN.c ukfCfgN.h)
Why this project is useful:
There is not any specific external dependency. All needed sources are available in repository.
Implementation could be easy adapted for every different nonlinear filtering problem only by creation of own ukfCfgN.c,ukfCfgN.h files.
Implementation follow the prety good Matthew Rhudy tutorial step by step and solve the same example. Users could easy compare the difference between matlab and C implementation.
The project contain simulink model(R2013b) which show how s-function could be created(s-function builder) and simulated from given set of source files. There is two steps needed to simulate UKF filter in Simulink. First step is to load data in WS by running of ukf.m. The second step is to build s-fun and run simulink model. Filter behavior could be checked at every simulation step and compared with expected data generated from m-script implementation(applied also in tutorial).

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Updates

1.2.0.0

Initial implementation on GUI tool for filter configuration and automatic file generation(ukfCfgN.c ukfCfgN.h)

1.1.0.0

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MATLAB Release Compatibility
Created with R2013b
Compatible with any release
Platform Compatibility
Windows macOS Linux

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