Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/1865
Title: Radar Emitter Classification Using Self-Organising Neural Network Models
Authors: Anjaneyulu, L.
Murthy, N.S.
Sarma, N.V.S.N.
Keywords: Artificial Neural Networks
Radar Emitter
Issue Date: 2008
Publisher: 2008 International Conference of Recent Advances in Microwave Theory and Applications, MICROWAVE 2008
Citation: 10.1109/AMTA.2008.4763033
Abstract: This paper presents a Radar Emitter Identification and Classification technique based on Fuzzy ART and ARTMAP Neural Networks. The radar emitter's parameters of RF, PW, PRJ, Direction of Arrival(DOA) etc., are taken as inputs for the networks. The network is trained with the available data of the emitter types. After training, the network is used to identify the emitter type by applying the parameters of the emitter as inputs to the neural network. A number of simulations are carried out and the simulated results show that the network quickly and accurately identify and classify the emitter types.
Description: NITW
URI: http://localhost:8080/xmlui/handle/123456789/1865
Appears in Collections:Electronics and Communication Engineering

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