Micro-Doppler Characteristics of mmWave Indoor Backscattering Channels for RF Sensing

• Published in: 2022 18th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob) pp. 357 - 362
• Main Authors: Avazov, Nurilla, Hicheri, Rym, Patzold, Matthias
• Format: Conference Proceeding
• Language: English
• Published: IEEE 10-10-2022
• Subjects: Backscattering; Channel models; Doppler radar; Frequency measurement; micro-Doppler signatures; millimeter wave communications; non-stationary indoor channels; Radar measurements; Radio frequency; Trajectory
• ISSN: 2160-4894
• DOI: 10.1109/WiMob55322.2022.9941610

In indoor environments, backscattering components play a key role in radio-frequency (RF) sensing, especially with the blockage of line-of-sight components by the furniture. Thus, it is paramount to investigate the Doppler characteristics of backscattering millimeter wave (mmWave) channels in the presence of moving objects. In this regard, this paper presents a trajectory-driven non-stationary channel model for a mmWave single-input single-output communication system. This backscattering channel model takes into account the impact of a single moving object on the indoor radio wave propagation phenomena. First, the expression of the complex channel gain is presented. Then, the time-variant (TV) micro-Doppler signatures of the moving object are studied. The validity of the proposed channel model is confirmed by real-world measured RF data, which were collected in a laboratory room using a software defined radar system operating at 24 GHz. For fair comparison, we consider as a moving object a swinging pendulum for which the exact TV trajectory is known. In addition, inertial measurement unit sensors are attached to the pendulum to track its TV trajectory. A good agreement can be seen between the Doppler characteristics of the backscattering channel model and those computed from the measured RF data. This demonstrates that backscattering components can be employed to accurately extract the micro-Doppler signatures of a moving object in indoor spaces. The exhibited results can serve as a basis for the development of future robust backscattering-based RF sensing.