  Estimating parameters and properties of various materials without causing
damage to the material under test (MUT) is important in many applications.
Thus, in this letter, we address this by wireless sensing. Here, the accuracy
of the estimation depends on the accurate estimation of the properties of the
reflected signal from the MUT (e.g., number of reflections, their amplitudes
and time delays). For a layered MUT, there are multiple reflections and, due to
the limited bandwidth at the receiver, these reflections superimpose each
other. Since the number of reflections coming from the MUT is limited, we
propose sparse signal processing (SSP) to decompose the reflected signal. In
SSP, a so called dictionary is required to obtain a sparse representation of
the signal. Here, instead of a fixed dictionary, a dictionary update technique
is proposed to improve the estimation of the reflected signal. To validate the
proposed method, a vector network analyzer (VNA) based measurement setup is
used. It turns out that the estimated dielectric constants are in close
agreement with the dielectric constants of the MUTs reported in literature.
Further, the proposed approach outperforms the state-of-the-art model-based
curve-fitting approach in thickness estimation.
