Abstract
In this paper, we propose a robust method for UWB automatic radar classification in white Gaussian noise and different aspect angles between the radar and the target. The method is based on the use of Matrix Pencil Method in Frequency Domain (MPMFD) for feature extraction and Mahalanobis Distance for classification. In order to test the accuracy of the proposed method, we have used complex target geometries modeled by perfectly conducting, straight, thin wires. Simulation results show that accurate results of radar target classification can be obtained by the proposed method. In addition, we prove that the proposed method has better ability to tolerate noise effects in radar target classification.
Sign-in/Register to access full text options 
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.
