DocumentCode
2438963
Title
Approaches on multi-sensor fusion under time-evolving conditions
Author
Luo, Ren C. ; Yang, W.S. ; Lin, Min-Hsiung
Author_Institution
Dept. of Electr. & Comput. Eng., North Carolina State Univ., Raleigh, NC, USA
fYear
1988
fDate
24-26 Aug 1988
Firstpage
159
Lastpage
164
Abstract
A paradigm for optimum estimation of fused multiple sensor data is developed in order to best use the sensor information in the time evolving environment. Two basic approaches have been developed: dynamic moving quadratic curve fitting and weighted least mean square error. These two approaches are shown to be advantageous in terms of accuracy, speed, and versatility. The theoretical frameworks presented are supported by sets of simulation data
Keywords
curve fitting; signal processing; dynamic moving quadratic curve fitting; multi-sensor fusion; optimum estimation; time-evolving conditions; weighted least mean square error; Intelligent robots; Intelligent sensors; Machine intelligence; Military aircraft; Mobile robots; Robot sensing systems; Sensor fusion; Sensor phenomena and characterization; Sensor systems; Uncertainty;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control, 1988. Proceedings., IEEE International Symposium on
Conference_Location
Arlington, VA
ISSN
2158-9860
Print_ISBN
0-8186-2012-9
Type
conf
DOI
10.1109/ISIC.1988.65423
Filename
65423
Link To Document