DocumentCode
3423377
Title
Intelligent PDAF: refinement of IPDAF for tracking in clutter
Author
Li, Ning ; Ning Li
Author_Institution
New Orleans Univ., LA, USA
fYear
1997
fDate
9-11 Mar 1997
Firstpage
133
Lastpage
137
Abstract
An intelligent probabilistic data association filter (IPDAF) is presented as a refinement of the original IPDAF developed by D. Musicki et al. (1994). The refinement includes the incorporation of measurement feature information, a better estimator of clutter density, and an important correction of a mistake in the original PDAF and IPDAF. Simulation results demonstrate the substantial superiority of the proposed IPDAF to the original one
Keywords
clutter; filters; knowledge based systems; probability; signal processing; target tracking; tracking; IPDAF refinement; clutter density; intelligent PDAF; intelligent probabilistic data association filter; measurement feature information; tracking in clutter; Computational modeling; Density measurement; Equations; Information filtering; Information filters; Measurement uncertainty; Nearest neighbor searches; Probability density function; State estimation; Target tracking;
fLanguage
English
Publisher
ieee
Conference_Titel
System Theory, 1997., Proceedings of the Twenty-Ninth Southeastern Symposium on
Conference_Location
Cookeville, TN
ISSN
0094-2898
Print_ISBN
0-8186-7873-9
Type
conf
DOI
10.1109/SSST.1997.581593
Filename
581593
Link To Document