Title :
Multi sensor data fusion using fuzzy-association techniques
Author :
Tummala, Murali ; Midwood, Sean A. ; Glenn, Ian N.
Author_Institution :
Dept. of Electr. & Comput. Eng., Naval Postgraduate Sch., Monterey, CA, USA
Abstract :
This paper describes the development of an algorithm to fuse redundant observations due to multiple sensor coverage of a vessel within the Vessel Traffic Services (VTS) system. Fuzzy membership functions are used as a measure of correlation, and a fuzzy associative system determines which observations represent the same vessel. The result is a computationally efficient algorithm. The output of the system is a unique set of vessels identified by unique platform identifiers. Results of tests based on computer simulation of overlapping radar coverage show that the fusion algorithm correctly correlates and fuses the sensor observations.
Keywords :
fuzzy set theory; marine systems; monitoring; radar applications; sensor fusion; Vessel Traffic Services; computationally efficient algorithm; fuzzy-association techniques; multiple sensor coverage; multisensor data fusion; overlapping radar coverage; redundant observations; unique platform identifiers; Computer simulation; Displays; Fuses; Fuzzy systems; Radar tracking; Sensor fusion; Sensor phenomena and characterization; Sensor systems; Software systems; Testing;
Conference_Titel :
Circuits and Systems, 1997. Proceedings of the 40th Midwest Symposium on
Print_ISBN :
0-7803-3694-1
DOI :
10.1109/MWSCAS.1997.662233