Open AccessTracking algorithm with radar and infrared sensors using a novel adaptive grid interacting multiple model
Author(s) -
Wu Panlong,
Li Xingxiu,
Zhang Lianzheng,
Bo Yuming
Publication year - 2014
Publication title -
iet science, measurement and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.418
H-Index - 49
eISSN - 1751-8830
pISSN - 1751-8822
DOI - 10.1049/iet-smt.2013.0020
Subject(s) - tracking (education) , radar , grid , computer science , infrared , radar tracker , algorithm , artificial intelligence , telecommunications , physics , optics , geology , geodesy , psychology , pedagogy
This study presents a novel adaptive grid interacting multiple model based on modified iterated extended Kalman filter (AGIMM‐MIEKF) for tracking a manoeuvreing target using radar/infrared (IR) heterogeneous sensors. This tracking algorithm is developed by aligning observation data of radar/IR sensors in time, and fusing the synthesised data before applying to AGIMM‐MIEKF algorithm. Under the architecture of the proposed algorithm, the AGIMM deals with the model switching, whereas the MIEKF accounts for non‐linearity in the dynamic system models. A new measurement update equation and an iterated termination criterion are derived and applied to radar/IR tracking system. The simulation results show that the presented AGIMM‐MIEKF has higher tracking precision than the traditional algorithms.