关键词: 无线传感器网络, 距离矢量跳定位法, 控制变量法, 待定系数法, 等效权重, 极大似然估计

Abstract: Focus on the low positioning accuracy and strong scene dependence of optimization strategy of the Distance Vector Hop (DV-Hop) localization model, an enhanced DV-Hop model——Function correction Distance Vector Hop (FuncDV-Hop) based on function analysis and simulated fixed parameters was presented. First, analysis was done on the average hop distance, distance estimate, and least square technique errors in the DV-Hop model. The following concepts were introduced: undetermined coefficient optimization, step function segmentation experiment, weight function approach using equivalent points, and modified maximum likelihood estimation. Then, in order to design control trials, the number of nodes, the proportion of beacon nodes, the communication radius, the number of beacon nodes, and the number of unknown nodes were all designed by using the control variable technique. Finally, the experiment was split into two phases: simulation with fixed parameters and integrated optimization testing. Compared with the original DV-Hop model, the positioning accuracy of the final improved strategy is improved by 23.70%~75.76%, and the average optimization rate is 57.23%. The experimental results show that, compared with the DV-Hop model based on genetic algorithm and neurodynamic improvement, the positioning accuracy of FuncDV-Hop model can be improved by more than 50%, the positioning error can be generally reduced by more than 10 percentage points, and the positioning accuracy can be improved by more than 10%. The proposed model does not introduce other parameters, does not increase the protocol overhead of wireless sensor networks, and effectively improves the positioning accuracy.

Key words: Wireless Sensor Network (WSN), Distance Vector Hop (DV-Hop) localization model, control variate method, method of undetermined coefficients, equivalent weight, maximum likelihood estimator