A Framework for Activity Monitoring and Fall Detection Based on the Characteristics of Indoor Channels

Abstract

This paper concerns the Doppler power spectrum of three-dimensional non-stationary indoor fixed-to- fixed channels with moving people. In this paper, we model each moving person as a moving scatterer with time-variant (TV) speed, TV vertical angles of motion, and TV horizontal angles of motion of the moving scatterers. Furthermore, we derive the TV angular parameters of each moving scatterer such as the elevation angle of departure, the azimuth angle of departure, the elevation angle of arrival, and the azimuth angle of arrival. In addition, the TV unit vectors of the departure of the transmitted wave planes and unit vectors of the arrival of the received wave planes are derived. Furthermore, to present the Doppler power spectrum characteristics of such channels, we provide the closed-form solution of the spectrogram of the complex channel gain. The correctness of the analysis is approved by simulations. The contribution of this paper is an initiative for the development of device-free indoor activity monitoring and fall detection systems.