A Novel Maneuvering Target Tracking Algorithm with Two Passive Sensors

Author

Li, Liang-qun ; Ji, Hong-bing

Author_Institution

Sch. of Electron. Eng., Xidian Univ., Xi´´an

Volume

4

fYear

2006

fDate

16-20 2006

Abstract

For maneuvering target tracking with two passive sensors in clutter environment, a novel tracking algorithm based on maximum entropy fuzzy clustering is proposed. Firstly, the interacting multiple models (IMM) approach is used to solve the maneuver problem of the target, and the false alarms generated by clutter are accommodated through maximum entropy fuzzy probabilistic data association filter (MEF-PDAF). Secondly, in order to avoid the unobservability problem of passive target tracking, a nonlinear measurement model of two passive sensors is founded. Finally, the simulation results show that the proposed algorithm has the advantages over the conventional IMM-PDAF algorithm in terms of simplicity and efficiency

Keywords

filtering theory; fuzzy set theory; maximum entropy methods; target tracking; clutter environment; interacting multiple models; maneuvering target tracking algorithm; maximum entropy fuzzy clustering; passive sensors; passive target tracking; probabilistic data association filter; Clustering algorithms; Data mining; Entropy; Equations; Filters; Kinematics; Measurement uncertainty; Personal digital assistants; Sensor phenomena and characterization; Target tracking;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing, 2006 8th International Conference on

Conference_Location

Beijing

Print_ISBN

0-7803-9736-3

Electronic_ISBN

0-7803-9736-3

Type

conf

DOI

10.1109/ICOSP.2006.346082

Filename

4129774