This paper investigates based on Received Signal Strength Indicator using particle filtering and three radio propagation models: the hybrid Two-Ray Ground Reflection model, the One-Slope, and the Two-Slope Log-Distance Path Loss models. To improve robustness against Received Signal Strength Indicator fluctuations, all three propagation models are used in a Sequential Importance Resampling particle filter for recursive state estimation. Experimental validation was conducted in an outdoor environment with ESP32-based Wi-Fi devices operating at 2.4 GHz, at antenna heights of 0.5 m, 1.0 m, and 1.5 m, and at distances up to 250 meters. The results show that model performance depends heavily on the distance range, antenna mounting height, and measurement conditions. Although the Two-Slope Log-Distance Path Loss model provided the best fit, none of the evaluated models accurately predicted the experimental data. Applying a Particle Filter consistently reduced variance and improved overall estimation stability. Among the evaluated combinations, the Two-Slope model paired with the Particle Filter yielded the most precise distance estimates.