Abstract
Accurate and high-resolution extraction of the Micro-Doppler (M-D) feature is of great significance for radar target identification. However, current feature extraction methods are usually based on the conventional time-frequency (TF) distributions (TFDs), which suffer from poor resolution or interference terms. Considering the inherent sparsity of the target echo on the TF plane, this paper proposes a novel TF analysis method named short-time sparse Fourier transform (STSFT) to enhance the M-D characteristics. Different from previous sparsity-based TF methods, the sparse constraint is added to each short-time signal segment individually. The effectiveness of the STSFT is validated by simulations.
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.
