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|Title:||Human detection with radar: Dismount detection||Authors:||Gürbüz, Sevgi Z.||Issue Date:||2013||Publisher:||Institution of Engineering and Technology||Abstract:||This chapter provides a brief overview of current systems and development efforts, kinematic and RCS models, technical challenges, and recently proposed novel ideas relating to human detection with radar. The expected radar return for a human target was analytically derived and the most widely used human kinematic model, the Boulic-Thalmann model, was described in detail. The concept of human micro-Doppler was introduced, along with the concept of human spectrograms and the application of spectrogram analysis for classification and identification of detected targets. Key technical challenges in human detection, such as the limitations of GMTI radars, STAP processors, and Fourier-based detectors, were presented, along with a brief introduction to knowledge-aided ideas that have been proposed as a solution to some of these issues. There has been much progress in the field of human detection. However, there remains much work to be done to fully resolve questions in human modeling, kinematics, radar cross section, dismount detection, and target classification algorithm design. Advanced topics beyond the scope of this chapter but that also constitute important applications of human radar detection include the following: through-the wall detection of humans, which aims at using ultra wideband radar to detect human respiration, for important applications, such as indoor surveillance and human search and rescue of fire and earthquake victim: synthetic aperture radar detection and imaging of human targets: radar networks for border security and surveillance. © 2013 SciTech Publishing, Edison, NJ. All rights reserved.||URI:||https://doi.org/10.1049/SBRA020E_16
|Appears in Collections:||Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering|
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
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