(Stuttgart : Fraunhofer-Institut für Produktionstechnik und Automatisierung IPA, 2023) Aziz, Fady Ashraf William; Huber, Marco (Univ.-Prof. Dr.-Ing. habil.)
The study of radar for human recognition based on deep learning is becoming increasingly popular. It has been demonstrated that the micro-Doppler (μ-D) spectrograms effect can reflect walking human gait by capturing the periodic micro-motions of the limbs. The research scope was extended to include human recognition for variable activities, and hence, a broad number of applications have been investigated, such as fall detection. In addition to this, there are two main factors that have introduced the radar as a powerful sensor for such applications. First is the radar detection capability that is not affected by any environmental limitations. Second, the multiple-input-multiple-output transmission protocol that enabled the radar detection and tracking for multiple humans.
