Time-Frequency Transforms for Radar Imaging and Signal Analysis - Chen, Victor C
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This text is a hands-on guide to time-frequency transforms for radar imaging and signal analysis. It explores more efficient ways to: extract dispersive scattering features; detect and extract weak signals in noise; form clear radar images; estimate parameters and perform motion compensation; detect and track moving targets in the synthetic aperture radar; and analyze vibration and rotation induced micro-Doppler. This resource introduces an image formation algorithm based on time-frequency-transforms, showing its advantage over the more conventional Fourier-based image formation. Referenced…mehr

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Produktbeschreibung
This text is a hands-on guide to time-frequency transforms for radar imaging and signal analysis. It explores more efficient ways to: extract dispersive scattering features; detect and extract weak signals in noise; form clear radar images; estimate parameters and perform motion compensation; detect and track moving targets in the synthetic aperture radar; and analyze vibration and rotation induced micro-Doppler. This resource introduces an image formation algorithm based on time-frequency-transforms, showing its advantage over the more conventional Fourier-based image formation. Referenced with over 170 equations and 80 illustrations, the book presents algorithms that help improve the result of radar imaging and signal processing. Moreover, the authors discuss future trends in time-frequency to analyze micro-Doppler, and provide a newly developed time-frequency approach to radar signal and image processing to help solve problems associated with conventional approaches.
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Autorenporträt
Victor C. Chen, electronic engineer in the Radar Division of the Naval Research Laboratory in Washington, DC, is a senior member of the IEEE, and a member of the SPIE. He received his Ph.D. and, M.S. Degree in Electrical Engineering from the Case Western Reserve University, Cleveland, OH. Hao Ling, professor in the department of electrical and computer engineering, University of Texas at Austin, is an IEEE Fellow. He earned his Ph.D. and M.S. in Electrical Engineering at the University of Illinois at Urbana-Champaign.