A Monte Carlo localization Algorithm based on Ranging

To overcome the limitations of the traditional Monte Carlo localization (MCL) algorithm, such as complex sampling processes and excessive energy consumption of nodes, this paper proposed an MCL algorithm based on ranging. The MCL-R introduces Received Signal Strength(RSS)values to modify the weights between the anchor nodes and the unknown nodes, and controls the sampling environment dynamically. The simulation results show that the proposed algorithm has a lower sampling time and a higher sampling rate, which reduces the energy consumption required for positioning computations in sensor networks.