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Straka Ondřej and Flídr Miroslav and Duník Jindřich and Šimandl Miroslav and Blasch Erik : Nonlinear estimation framework in target tracking . Proceedings of the 13th International Conference on Information Fusion, Edinburgh, UK, 2010.


The goal of the article is to describe a software framework designed for nonlinear state estimation of discrete-time dynamic systems. The framework was designed with the aim to facilitate implementation, testing and use of various nonlinear state estimation methods. The main strength of the framework is its versatility due to the possibility of either structural or probabilistic model description. Besides the well-known basic nonlinear estimation methods such as the extended Kalman filter, the divided difference filters and the unscented Kalman filter, the framework implements the particle filter with advanced features. As the framework is designed on the object oriented basis, further extension by user-specified nonlinear estimation algorithms is extremely easy. The paper describes the individual components of the framework, their key features and use. The paper demonstrates easy and natural application of the framework in target tracking which is illustrated in two examples - tracking a ship with unknown control and tracking three targets based on raw data.

Detail of publication

Title: Nonlinear estimation framework in target tracking
Author: Straka Ondřej ; Flídr Miroslav ; Duník Jindřich ; Šimandl Miroslav ; Blasch Erik
Language: English
Year: 2010
Type of publication: Papers in proceedings of reviewed conferences
Title of journal or book: Proceedings of the 13th International Conference on Information Fusion
Address: Edinburgh, UK
Date: 29 Jul 2010
2011-03-15 16:21:57 / 2011-03-15 16:21:57 / 1


Nonlinear state, parameter estimation, Bayesian approach, Tracking, EKF, UKF, Particle filter.


 author = {Straka Ond\v{r}ej and Fl\'{i}dr Miroslav and Dun\'{i}k Jind\v{r}ich and \v{S}imandl Miroslav and Blasch Erik},
 title = {Nonlinear estimation framework in target tracking},
 year = {2010},
 journal = {Proceedings of the 13th International Conference on Information Fusion},
 address = {Edinburgh, UK},
 url = {},