Received Signal Strength (RSS) for indoor localization is widely used due to its simplicity and availability in most mobile devices. The RSS channel model is defined by the propagation losses and the shadow fading. This paper studies two-slope RSS channel model and compares its validity to classical one-slope path loss model. Particularly, the work presents real-data results of a Bayesian calibration method. Validation of the model fitting is then performed in a dynamic scenario where the distance to a reference node is tracked by a Kalman Filter. Results show the superiority of two-slope model, specially at large distances.