DocumentCode :
2066352
Title :
Estimation with particle filter under model uncertainty
Author :
Bo, Yang ; Shuxia, Guo ; Ning, Liu ; Jun, Hao
Author_Institution :
Nat. Key Lab. of Sci. & Technol. on UAV, Northwestern Polytech. Univ., Xi´´an, China
fYear :
2011
fDate :
14-16 Sept. 2011
Firstpage :
1
Lastpage :
5
Abstract :
A new method for estimation under model uncertainty is proposed. Section 1 defined the problem and introduced algorithms invented before. Section 2 pointed out the limitation of exist methods and presented ours. The core is that we treat unknown model mode as sample of an infinite model mode set. After properly modeled, section 3 presented particle filter based computation algorithm for our model. Section 4 provide a demonstration example and shows when adopt our method, model uncertainty problem can be solved with good efficiency. Section 5 concludes preliminarily that the proposed algorithm is promising.
Keywords :
particle filtering (numerical methods); computation algorithm; infinite model mode set; model uncertainty; particle filter; Adaptation models; Computational modeling; Estimation; Mathematical model; Particle filters; Signal processing algorithms; Uncertainty; estimation; model uncertainty; particle filter;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing, Communications and Computing (ICSPCC), 2011 IEEE International Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-4577-0893-0
Type :
conf
DOI :
10.1109/ICSPCC.2011.6061671
Filename :
6061671
Link To Document :
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