Abstract: In multi-sensor networks，range-based localization is a common means of target localization；However，because of some interference such as the system’s equipment and environmental factors，it will have a range of data errors which affect localization accuracy.At present，there is no better way to eliminate error；Certain specific algorithms can only be applied to minimize the error of localization accuracy.This paper presents a measurement error based on the statistical characteristics of obedience probability algorithm，first according to all the location data，fitting-out the initial estimates point，then take the initial estimates point as the center position of the selected regional rectangular grid，each a small grid on behalf of the center of the small grid，and through the perception of all the nodes 3-3 portfolio Statistics small mesh weights，weights to the largest point as a target point.Through the MATLAB software programming and simulation results show that the algorithm can effectively improve positioning accuracy.

摘要： 在多传感器网络中，测距定位是目标定位的一种常用手段，但是由于系统设备和环境干扰等因素的影响，使得测距数据产生误差，影响定位精度。目前还没有更好的方法用来消除误差，只能应用某些特定的算法，来尽量减少测距误差对定位精度的影响。提出了一种基于测量误差服从概率统计特性的算法，首先根据所有测距数据，拟合出初始概位点，以初始概位点为中心，选取矩形区域并网格化，以每一个小网格的中心点代表该小网格，再通过所有感知节点的3-3组合，统计小网格的权值，以权值最大点作为目标定位点。通过在MATLAB软件包中编程并仿真实验，结果表明，该算法可有效地提高定位精度。