As a typical pattern recognition problem, specific emitter identification (SEI) is a crucial step to achieve efficient spectrum sensing. In this work, an emitter identification method based on Signal Graph Capsule Network, which refered as SGCN, is proposed. First, emitter signal is transformed into an undirected graph according to the Euclidean distance from its sampling point, and then take the undirected graph as the input of the network. Second, optimizing the topological structural characteristics by graph convolution operation on this undirected graph. Finally, by introduce the capsule network to improve the generalization ability and enhance the robustness. Extensive analysis and experiments on 30 individual emitters signals demonstrates the attentiveness of the proposed model.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.