3D imaging from multipath temporal echoes

The dataset contains 3 datasets: - One labelled 'simulated' - One labelled 'RF' (radio frequency) - One labelled 'acoustic' All 3 datasets consist of signals reflected off of an enclosed scene, and measured in the temporal domain with no spatial structure in the measurement, as well as a corresponding 3D image. The simulated data was generated using a computer simulation. The RF and acoustic data were experimentally measured. These datasets each contained temporal signals of a participant in their residential rooms, as well as simultaneous 3D images of the participant and room. To gather temporal data, one participant was subjected to sound waves, while the second was illuminated with radio frequency (RF) waves. Neither radiation poses any danger to humans, on account of the low power used. The sonic and RF waves reflected off the targets and the surrounding environment, and were detected using a microphone and a RADAR system respectively. To gather 3D images, the participants were simultaneously imaged using a LiDAR system. The dataset contains additional machine learning code used to infer the 3D images of the scene from the corresponding sonic, RF and simulated data. Finally, the dataset contains the figures and videos used in the corresponding journal article '3D imaging from multipath temporal echoes'. The purpose of the dataset is to give the public open access to the research data in said publication.