Title :
Unified optimal linear estimation fusion. II. Discussions and examples
Author :
Li, X. Rong ; Wang, Jie
Author_Institution :
Dept. of Electr. Eng., New Orleans Univ., LA, USA
Abstract :
For pt.I see ibid., p.MOC2 10-17. Several unified optimal estimation/track fusion rules in the sense of best linear unbiased estimation (BLUE) and weighted least squares (WLS) have been presented in pt.I for centralized, distributed, and hybrid fusion architectures. This paper discusses their pros and cons, verifies these rules, and demonstrate via simulation examples how these fusion rules can be used in cases with either complete, incomplete, or no prior information about the estimate (i.e., the quantity to be estimated).
Keywords :
estimation theory; sensor fusion; statistical analysis; BLUE; MMSE estimation; best linear unbiased estimation; estimation fusion; fusion architectures; fusion rules; optimal estimation; track fusion; unified optimal linear estimation fusion; weighted least squares; Computer architecture; Data models; Distributed computing; Equations; Estimation error; Least squares approximation; Sensor fusion;
Conference_Titel :
Information Fusion, 2000. FUSION 2000. Proceedings of the Third International Conference on
Conference_Location :
Paris, France
Print_ISBN :
2-7257-0000-0
DOI :
10.1109/IFIC.2000.862452
