The demands on indoor localization services have grown explosively due to increasing popularity of mobile devices. Though various techniques based on wireless signals have been proposed, the new Bluetooth 4.0 and 4.1 technologies introduce both opportunities and challenges for localization. Like all wireless signals, the fluctuations caused by hardware conditions and environmental dynamics may deteriorate the accuracy of localization. Therefore, we propose to use adaptive ranging, which utilizes inter-beacon measurements to 'sense' the transient device and environmental conditions, and adjust the parameters of signal propagation model. In this research, we apply this concept to multi-lateration and mobile encountering for localization using Bluetooth advertisements. We also validate that with the proposed adaptive ranging techniques, the impacts of signal fluctuations caused by hardware and environmental conditions can be greatly decreased. Furthermore, we combine the adaptive multi-lateration, encountering mechanism and pedestrian dead-reckoning with a particle filter (PF) framework to generate our localization results. Finally, two sets of experiments are performed in a department building. The overall improvement in accuracy is approximately 19.99% using our adaptive localization when comparing to the conventional non-Adaptive methods.