Title :
Intelligent PDAF: refinement of IPDAF for tracking in clutter
Author :
Li, Ning ; Ning Li
Author_Institution :
New Orleans Univ., LA, USA
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;
Conference_Titel :
System Theory, 1997., Proceedings of the Twenty-Ninth Southeastern Symposium on
Conference_Location :
Cookeville, TN
Print_ISBN :
0-8186-7873-9
DOI :
10.1109/SSST.1997.581593
