Software
The IDM Research Team develops a complex software packages that implements the majority of state estimation algorithms. The packages enables to fully describe the estimation problem, i.e. the data generator, its model and the method of estimation. Based on the results, the package can provide a complex evaluation of estimation quality including a comparison of individual methods' performance.
Accompanying MATLAB® m-files
2023
Matoušek J., Duník J., & Brandner M.. Design of Efficient Point-Mass Filter with Application in Terrain Aided Navigation. In review for FUSION 2023. m-files download
2019
Duník, J., Kost, O., Straka, O., & Blasch E.. Covariance Estimation and Gaussianity Assessment for State and Measurement Noise. Journal of Guidance, Control, and Dynamics. m-files download
2017
Duník, J., Straka, O., Kost, O., & Havlík, J.. Noise covariance matrices in state-space models: A survey and comparison of estimation methods—Part I. Int. J. Adapt. Control Signal Process., 31(11): 1505–1543, 2017. doi:10.1002/acs.2783. m-files download
