Aiming at the problems of the current self-localization algorithms for indoor mobile robot, such as the low positioning accuracy, increasing positioning error with time, the signal's multipath effect and non-line-of-sight effect, a new mobile robot self-localization method based on Monte Carlo Localization (MCL) was proposed. Firstly, through analyzing the mobile robot self-localization system based on Radio Frequency IDentification (RFID), the robot motion model was established. Secondly, through the analysis of the mobile robot positioning system based on Received Signal Strength Indicator (RSSI), the observation model was put forward. Finally, in order to improve the computing efficiency of particle filter, the particle culling strategy and particle weight strategy considering orientation of the particles were given, to enhance the positioning accuracy and the execution efficiency of the new positioning system. The position errors of the new algorithm were about 3 cm in both the X direction and the Y direction, while position error of the traditional localization algorithm in the X direction and the Y direction were both about 6 cm. Simulation results show that the new algorithm doubles the positioning accuracy, and has good robustness.