| Titre : | Computationally efficient multisensor fusion estimation algorithms (2010) |
| Auteurs : | Seokhyoung Lee, Auteur ; Vladimir Shin, Auteur |
| Type de document : | Article : texte imprimé |
| Dans : | Transactions of the ASME . Journal of dynamic systems, measurement, and control (Vol. 132 N° 2, Mars/Avril 2010) |
| Article en page(s) : | 04 p. |
| Note générale : | Systèmes dynamiques |
| Langues : | Anglais |
| Index. décimale : | 629.8 |
| Tags : | Approximation theory Covariance matrices Sensor fusion |
| Résumé : | This paper provides two computationally effective fusion estimation algorithms. The first algorithm is based on Cholesky factorization of a cross-covariance block matrix. This algorithm has low computational complexity and is equivalent to the standard composite fusion estimation algorithm as well. The second algorithm is based on a special approximation scheme for local cross-covariances. Such approximation is useful to compute matrix weights for fusion estimation in a multidimensional-multisensor environment. Subsequent computational analysis of the proposed fusion algorithms is presented with corresponding examples showing the low computational complexities of the new fusion estimation algorithms. |
| DEWEY : | 629.8 |
| ISSN : | 0022-0434 |
| En ligne : | http://asmedl.aip.org/getabs/servlet/GetabsServlet?prog=normal&id=JDSMAA000132000002024503000001&idtype=cvips&gifs=Yes&ref=no |
