  This paper introduces an indoor localization method using fixed reflector
objects within the environment, leveraging a base station (BS) equipped with
Angle of Arrival (AoA) and Time of Arrival (ToA) measurement capabilities. The
localization process includes two phases. In the offline phase, we identify
effective reflector points within a specific region using significantly fewer
test points than typical methods. In the online phase, we solve a maximization
problem to locate users based on BS measurements and offline phase information.
We introduce the reflectivity parameter (\(n_r\)), which quantifies the typical
number of first-order reflection paths from the transmitter to the receiver,
demonstrating its impact on localization accuracy. The log-scale accuracy ratio
(\(R_a\)) is defined as the logarithmic function of the localization area
divided by the localization ambiguity area, serving as an accuracy indicator.
We show that in scenarios where the Signal-to-Noise Ratio (SNR) approaches
infinity, without a line of sight (LoS) link, \(R_a\) is upper-bounded by \(n_r
\log_{2}\left(1 +
\frac{\mathrm{Vol}(\mathcal{S}_A)}{\mathrm{Vol}(\mathcal{S}_{\epsilon}(\mathcal{M}_s))}\right)\).
Here, \(\mathrm{Vol}(\mathcal{S}_A)\) and
\(\mathrm{Vol}(\mathcal{S}_{\epsilon}(\mathcal{M}_s))\) represent the areas of
the localization region and the area containing all reflector points with a
probability of at least \(1 - \epsilon\), respectively.
