Reflection Point Localization Without Prior Environmental Knowledge

In this paper, we present a novel measurement-driven ray tracing approach for estimating the location of a reflection point due to single-bounce reflections (SBRs). This approach requires no prior environmental information, such as floor plans. Instead, it formulates an optimization problem that aligns the parameters of an empirical fading model with time-series data of user-induced power changes. In addition to locating the reflection points (RPs), the method simultaneously estimates key parameters of the underlying model. The performance of the proposed approach is evaluated numerically based on Cramer-Rao lower bounds. Further, the effectiveness of the proposed method is demonstrated with ultra-wideband measurement data collected in an indoor environment. Results indicate that the proposed approach yields highly accurate RP location estimates, with minimal deviations from the true signal propagation paths. A comparison between the modeled power changes and the actual measured time-series data reveals strong agreement, underlining the robustness and applicability of the proposed method. This evaluation confirms that the approach provides a reliable solution for RP location estimation and model parameter extraction, even in scenarios lacking prior environmental knowledge.