DocumentCode
2497472
Title
An improved robust fusion method based on density estimation
Author
Guo, Yunfei ; Xue, Anke ; Lin, Yuesong ; Peng, DongLiang
Author_Institution
Inst. of Inf. & Control Technol., Hangzhou Dianzi Univ., Hangzhou
fYear
2008
fDate
25-27 June 2008
Firstpage
7576
Lastpage
7581
Abstract
To solve the uncertain information fusion problem, we define the robust performance of the fusion algorithm and propose an improved density estimation based robust fusion algorithm. First, the mean-shift procedure is employed in detecting the dominant mode of the information density function; second, the max iterative time is calculated according to the real time request; last, all the valid data in the dominant field after the max iterative time are fused. The presented algorithm is compared with the weighted fusion method and the density estimation fusion technique in two simulation cases. The results show that it is more accurate and robust and satisfies the system real time request.
Keywords
information theory; sensor fusion; density estimation fusion; information density function; max iterative time; mean-shift procedure; robust fusion algorithm; uncertain information fusion prolem; weighted fusion method; Automation; Density functional theory; Intelligent control; Iterative algorithms; Kernel; Real time systems; Robust control; Robustness; density estimation; robust fusion; uncertain information;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
Conference_Location
Chongqing
Print_ISBN
978-1-4244-2113-8
Electronic_ISBN
978-1-4244-2114-5
Type
conf
DOI
10.1109/WCICA.2008.4594105
Filename
4594105
Link To Document