DocumentCode :
2626845
Title :
An fuzzy IMM method for tracking micro reentering USV with TDRS
Author :
Pu Huang ; Li-Qiang Hou ; Guang-Dong Liang ; Ying Gao
Author_Institution :
State Key Lab. of Astronaut. Dynamics, Xi´an, China
fYear :
2011
fDate :
27-29 June 2011
Firstpage :
2039
Lastpage :
2046
Abstract :
Both kinematics and measurement model help process the trajectory data and estimate aerodynamic parameters of vehicle. In this paper, three dynamics are proposed, which are aerodynamics parameter´s model, acceleration´s model and α - β - γ model. The measurement model is TDRS (Tracking and Data Relay Satellite), which produces a complicated trajectory in reentering purpose. A fuzzy IMM algorithm is proposed in this paper, which through a fuzzy inference to get the matching degree of every UKF filtering model, instead of calculating model transition probabilities in IMM. With the matched degrees, the estimation from each filtering is weighted to get maneuvering target overall estimation and its covariance. Simulation results show that the FIMM algorithm performs well in tracking re-entering vehicle and estimating the aerodynamics parameters as well.
Keywords :
Kalman filters; aerodynamics; fuzzy set theory; remotely operated vehicles; satellite tracking; space vehicles; target tracking; α - β - γ model; TDRS; UKF filtering model; acceleration model; aerodynamic parameter; fuzzy IMM method; fuzzy inference; kinematics; maneuvering target; matching degree; measurement model; microreentering USV; tracking-and-data relay satellite; trajectory data; unmanned space vehicle; Aerodynamics; Atmospheric modeling; Electronic mail; Filtering; Vehicle dynamics; Vehicles; Aerodynamics; Fuzzy IMM; Reentry Vehicle; Tracking Target;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Service System (CSSS), 2011 International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-9762-1
Type :
conf
DOI :
10.1109/CSSS.2011.5975023
Filename :
5975023
Link To Document :
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