中文摘要：

针对蒙特卡洛盒（MCB）移动定位算法中存在的样本点退化问题，提出一种改进的蒙特卡洛盒（IMC定位算法，将其应用于无线传感器网络节点定位中。在MCB算法的基础上，通过分析当前时刻定位结果、节点距离以及相对位置信息，获得下一时刻在样本盒不同区域的采样概率，使样本点尽可能落在后验概率较大的区域内，从而解决MCB算法样本点退化导致定位精度降低的问题。仿真实验结果表明，在相同条件下，与MCB、MCL算法相比，IMCB算法的平均定位精度提高约14％，平均定位能耗降低约17％。

英文摘要：

Due to the problem of sample degeneration in Monte-Carlo Box（MCB） mobile localization algorithm, a new localization algorithm named Improved Monte-Carlo Boxed（IMCB） is proposed, which is applied to node localization of Wireless Sensor Network（WSN）. Based on the MCB algorithm, through analyzing the localization results of current time, distance between nodes and the information of node relative position to obtain the sampling probability of different regional of sample box for next time, the sample points can fall in the area where the posterior probability is large as much as possible, therefore the problem of low accuracy caused by sample degeneration in MCB algorithm is solved effectively. Simulation results show that, under the same conditions, the average localization accuracy is improved by about 14%, and the average energy consumption for localization is reduced by about 17% by comparing with the MCB, MCL algorithm.