Through-the-Wall Radar Imaging
Through-the-wall radar imaging is an emerging new technology allowing to “see” through obstacles such as walls, doors and other visually opaque materials. It covers a broad range of applications in a variety of contexts, such as fire and rescue missions, police missions and more recently in elderly care.
The Signal Processing Group has strong connections with the Center for Advanced Communications at Villanova University, Villanova, PA, USA, where real measurements are acquired in the Radar Imaging Lab.
The focus of our work is mainly in analysis and processing of through-the-wall radar images, including image formation or beamforming, multipath exploitation, compressive sensing, detection, segmentation, feature extraction and classification.
For more information on through-the-wall radar imaging, see the sections below or contact the respective Research Associates.
Among seniors aged 65 and older, falls are the main cause of accidental death. Facing an aging population, the number of falls, leading to fatal or nonfatal injuries, is continuously increasing. Besides preventing falls, timely and accurate detection of falls is desirable such that immediate assistance can be provided and long-term health limitations are minimized.
The aim is to enable elderly people to live self-dependent in their own homes or residences, while they are taken care of in case of an accidental fall. Here, radar-based fall detection systems are highly preferable over e.g. video surveillance or acoustic systems, as radar can operate in poor lighting conditions and highly noisy environments while preserving privacy concerns.
Radar-based fall detection systems send out electromagnetic waves and analyze the back-scattered signal. The moving body parts of a person, e.g. swinging arms and legs, lead to frequency shifts in the radar return signal due to the micro-Doppler effect. In the time-frequency representation they form the so-called micro-Doppler signatures. From these, a human activities, such as a fall, can automatically be detected and an emergency call can be made.
For more information on this research project or enquiries about Bachelor/Master thesis or Pro-/Project-Seminars, contact Ann-Kathrin Seifert.