基于经验的传播模型在实际应用中存在多值问题，导致RSSI 与距离并非一一映射。本文提出了一种改进的 MDS-MAP 定位算法，该算法利用基于距离区间概率的测距模型，消除多值问题对测距模型精度的影响，从而提高测距模型 的测量精度。通过仿真结果表明，改进的算法与传统的MDS-MAP 定位算法相比，算法具有更好的定位精度。

The propagation model based on experience has multi-valued problems in the practical application, which causes the RSSI and the distance not one- to-one mapping. This paper proposes an improved MDS-MAP localization algorithm, which uses propagation model based on distance interval ranging probability to eliminate the influence of multi-valued problems to ranging accuracy of the model, thereby improving measurement accuracy of ranging model. The simulation results show that the improved algorithm has better positioning accuracy when compared with the traditional MDS - MAP localization algorithm.