Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6117
Title: A Nonlinear-Phase Model-Based Human Detector for Radar
Authors: Gürbüz, Sevgi Z.
Melvin, William L.
Williams, Douglas B.
Keywords: [No Keywords]
Issue Date: 2011
Publisher: IEEE-Inst Electrical Electronics Engineers Inc
Abstract: Radar offers unique advantages over other sensors for the detection of humans, such as remote operation during virtually all weather and lighting conditions, increased range, and better coverage. Many current radar-based human detection systems employ some type of Fourier analysis, such as Doppler processing. However, in many environments, the signal-to-noise ratio (SNR) of human returns is quite low. Furthermore, Fourier-based techniques assume a linear variation in target phase over the aperture, whereas human targets have a highly nonlinear phase history. The resulting phase mismatch causes significant SNR loss in the detector itself. In this paper, human target modeling is used to derive a more accurate nonlinear approximation to the true target phase history. The likelihood ratio is optimized over unknown model parameters to enhance detection performance. Cramer-Rao bounds on parameter estimates and receiver operating characteristic curves are used to validate analytically the performance of the proposed method and to evaluate simulation results.
URI: https://hdl.handle.net/20.500.11851/6117
ISSN: 0018-9251
1557-9603
Appears in Collections:Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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