Integrating efficient connectivity, positioning and sensing functionalities
into 5G New Radio (NR) and beyond mobile cellular systems is one timely
research paradigm, especially at mm-wave and sub-THz bands. In this article, we
address the radio-based sensing and environment mapping prospect with specific
emphasis on the user equipment (UE) side. We first describe an efficient
l1-regularized least-squares (LS) approach to obtain sparse range--angle charts
at individual measurement or sensing locations. For the subsequent environment
mapping, we then introduce a novel state model for mapping diffuse and specular
scattering, which allows efficient tracking of individual scatterers over time
using interacting multiple model (IMM) extended Kalman filter and smoother. We
provide extensive numerical indoor mapping results at the 28~GHz band deploying
OFDM-based 5G NR uplink waveform with 400~MHz channel bandwidth, covering both
accurate ray-tracing based as well as actual RF measurement results. The
results illustrate the superiority of the dynamic tracking-based solutions,
compared to static reference methods, while overall demonstrate the excellent
prospects of radio-based mobile environment sensing and mapping in future
mm-wave networks