Title :
Statistical cluster analysis approach to sensor fusion problem
Author :
Pinsky, A. ; Eskin, M. ; Soroka, Y.
Author_Institution :
Lahav Div., Israel Aircraft Ind. Ltd., Israel
Abstract :
The sensor fusion (SF) problem, where it is required to estimate the number and the location of objects from their location measurements received from multiple independent sensors, is considered. This problem is solved using the cluster analysis method. We have applied multihypotheses testing techniques to the cluster analysis problem and have developed a decision rule which assures that the probability of false objects generation is not greater than any given significance level, while the possibility to omit existing objects decreases with more precise measurements. Object location estimates are also obtained. The computation algorithm that implements the above decision rule is developed
Keywords :
decision theory; heuristic programming; object recognition; probability; recursive functions; sensor fusion; statistical analysis; computation algorithm; decision rule; location of objects; military surveillance systems; multihypotheses testing; multiple independent sensors; probability of false objects generation; recursion formula; recursive algorithm; sensor fusion problem; significance level; statistical cluster analysis approach; Aerospace electronics; Aerospace engineering; Aerospace industry; Aircraft propulsion; Clustering algorithms; Inference algorithms; Military computing; Sensor fusion; Systems engineering and theory; Testing;
Conference_Titel :
Aerospace and Electronics Conference, 1997. NAECON 1997., Proceedings of the IEEE 1997 National
Conference_Location :
Dayton, OH
Print_ISBN :
0-7803-3725-5
DOI :
10.1109/NAECON.1997.622733
