In this paper, models of jamming signals are established based on the mechanism of active jamming signals against LFM radar. Five time-domain characteristics and frequency-domain characteristics of jamming signals are extracted. The decision tree method, BP neural network method and decision tree support vector machine (DTSVM) method are used to establish the classification models, and the simulation is performed for identifying and classifying the jamming signals at different jamming-to-noise ratio (JNR). The result shows that the model based on DTSVM method has better adaptability, smaller calculation and higher recognition success rate at low JNR.
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.