We introduce in this paper two main approaches, Triangulateration (TL) and Angle-Difference-of-Arrival (ADoA) for indoor localization and mapping using single-anchor and millimeter wave (MMW) propagation characteristics. Then, we perform context inference through obstacle localization. To do so, we first include and estimate the positions of virtual anchor nodes (VANs), known as mirrors of the real anchor with respect to obstacle. Then, it is followed by estimating the obstacle position and its dimensions. We assess the performance of each technique via cumulative distribution function (CDF) for the location estimation root mean square error (RMSE). Simulations confirm that localization of the receiver relying on a single anchor and the localization of obstacles in MMW achieves a few centimeters accuracy.