Title :
Target passive tracking based on Strong Tracking Filter
Author_Institution :
Dept. of Command Autom., Naval Univ. of Eng., Wuhan, China
Abstract :
We put forward Adaptive PLE (APLE) based on Strong Tracking Filter (STF) for bearing and frequency measure in order to rectify the bias of PLE. Furthermore, the APLE avoids filter divergence in that it is not necessary to linearize non-linear measure equation. Simulation demonstrate that the APLE has the ability to reduce estimate bias adaptively and estimate accuracy can be greatly improved.
Keywords :
adaptive Kalman filters; machine bearings; motion estimation; passive filters; target tracking; tracking filters; APLE; adaptive PLE; bearing; frequency measurement; strong tracking filter; target motion analysis; target passive tracking; Area measurement; Maximum likelihood estimation; Sonar measurements; adaptive filtering; passive tracking; strong tracking filter; target motion analysis;
Conference_Titel :
Computer Science and Information Technology (ICCSIT), 2010 3rd IEEE International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-5537-9
DOI :
10.1109/ICCSIT.2010.5564432