About: Nonlinear estimation framework in target tracking

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An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

Attributes	Values
rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
rdfs:seeAlso	http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5712076
Description	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. 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. (en)
Title	Nonlinear estimation framework in target tracking Nonlinear estimation framework in target tracking (en)
skos:prefLabel	Nonlinear estimation framework in target tracking Nonlinear estimation framework in target tracking (en)
skos:notation	RIV/49777513:23520/10:43898280!RIV14-MSM-23520___
http://linked.open...avai/riv/aktivita	P S
http://linked.open...avai/riv/aktivity	P(1M0572), P(GA102/08/0442), S
http://linked.open...vai/riv/dodaniDat	2014
http://linked.open...aciTvurceVysledku	Flídr, Miroslav Šimandl, Miroslav Straka, Ondřej Duník, Jindřich
http://linked.open.../riv/druhVysledku	D - Článek ve sborníku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Západočeská univerzita v Plzni / Fakulta aplikovaných věd
http://linked.open...dnocenehoVysledku	275037
http://linked.open...ai/riv/idVysledku	RIV/49777513:23520/10:43898280
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	Particle filter.; UKF; EKF; Tracking; Bayesian approach; Nonlinear state and parameter estimation (en)
http://linked.open.../riv/klicoveSlovo	Bayesian approach EKF Tracking Nonlinear state and parameter estimation UKF Particle filter.
http://linked.open...ontrolniKodProRIV	[91C39755078D]
http://linked.open...v/mistoKonaniAkce	Edinburgh, UK
http://linked.open...i/riv/mistoVydani	Piscataway
http://linked.open...i/riv/nazevZdroje	Proceedings of the 13th International Conference on Information Fusion
http://linked.open...in/vavai/riv/obor	BC
http://linked.open...ichTvurcuVysledku	4 (xsd:int)
http://linked.open...cetTvurcuVysledku	5 (xsd:int)
http://linked.open...vavai/riv/projekt	Data, algorithms, decision making Feasible approximations of dual control strategies
http://linked.open...UplatneniVysledku	2010
http://linked.open...iv/tvurceVysledku	Straka, Ondřej Šimandl, Miroslav Duník, Jindřich Flídr, Miroslav Blasch, Erik
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open.../riv/zahajeniAkce	2010-07-26 (xsd:date)
number of pages	8 (xsd:int)
http://purl.org/ne...btex#hasPublisher	IEEE
https://schema.org/isbn	978-0-9824438-1-1
http://localhost/t...ganizacniJednotka	23520

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