Title :
Neural blind separation for electromagnetic source localization and assessment
Author :
Albini, L. ; Burrascano, P. ; Cardelli, E. ; Faba, A. ; Fiori, S.
Author_Institution :
Dept. of Ind. Eng., Perugia Univ., Italy
fDate :
6/24/1905 12:00:00 AM
Abstract :
We present a possible approach to electromagnetic source localization using a hybrid blind separation-minimum search inversion algorithm. The total electrical field versus time emitted by the working antennas, located at different and unknown geographical positions, is used to reconstruct each separate contribution via a suitable neural network technique. When the emitted electric field and the related base frequencies have been separated for each emitting antenna, the unknown location of each emitter, is determined with a minimum-search numerical technique. The theory presented has been applied with success to a practical problem dealing with amplitude-modulated radio-transmissions
Keywords :
amplitude modulation; neural nets; radiocommunication; random processes; search problems; signal processing; amplitude-modulated radio-transmissions; antennas; base frequencies; electric field; electromagnetic source assessment; electromagnetic source localization; minimum search inversion algorithm; neural blind separation; Antenna measurements; Electric variables measurement; Electromagnetic fields; Electromagnetic measurements; Frequency; Interference; Neural networks; Radio control; Source separation; Time measurement;
Conference_Titel :
Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-7278-6
DOI :
10.1109/IJCNN.2002.1005506