Abstract
In this paper, for radar signals with different ways of frequency or phase modulation, Cascade of Short Time Fourier Transform (STFT) and Principal Component Analysis (PCA) is employed for effective Feature Extraction. Compressive ratios of dimensions are quite impressive. For the same features, applying Naive Bayes on the whole set of radar signals, higher accuracy rate is got than the case where classifier is SVM. Besides, a Hierarchical Structure is designed for finer classifications of radar signals. Comparison shows that Hierarchical Structure contributes little to increase of accuracy rate of radar signal classification by cascade systems on the whole set. Models are trained on 10db and tested on different Signal Noise Ratios (SNR).
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
