A comprehensive ultra-wideband dataset for non-cooperative contextual sensing.

Nowadays, an increasing amount of attention is being devoted towards passive and non-intrusive sensing methods. The prime example is healthcare applications, where on-body sensors are not always an option or in other applications which require the detection and tracking of unauthorized (non-cooperative) targets within a given environment. Therefore, in this paper we present a dataset consisting of measurements obtained from Radio-Frequency (RF) devices. Essentially, the dataset consists of Ultra-Wideband (UWB) data in the form of Channel Impulse Response (CIR), acquired via a Commercial Off-the-Shelf (COTS) UWB equipment. Approximately 1.6 hours of annotated measurements are provided, which are collected in a residential environment. This dataset can be used to passively track a target's location in an indoor environment. Additionally, it can also be used to advance UWB-based Human Activity Recognition (HAR) since three basic human activities were recorded, namely, sitting, standing and walking. We anticipate that such datasets may be utilized to develop novel algorithms and methodologies for healthcare, smart homes and security applications.