It has been shown that remote monitoring of pulmonary activity can be achieved using ultra-wideband (UWB) systems, which shows promise in home healthcare, rescue, and security applications. In this paper, a geometry-based statistical channel model is developed for simulating the reception of UWB signals in the indoor propagation environment. This model enables replication of time-varying multipath profiles due to the displacement of a human chest. Subsequently, a UWB distributed cognitive radar system (UWB-DCRS) is developed for the robust detection of chest cavity motion and the accurate estimation of respiration rate. The analytical framework can serve as a basis in the planning and evaluation of future measurement programs.
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