Title :
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
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;
Conference_Titel :
Signal Processing, 2006 8th International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-9736-3
Electronic_ISBN :
0-7803-9736-3
DOI :
10.1109/ICOSP.2006.346082
