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针对无线传感器网络中DV-Hop定位算法的不足,提出一种基于迭代协作的优化算法(ICDV-Hop算法)。通过限制跳数来减小距离误差,利用共线度测试约束节点间几何位置关系,选择最优信标三角形组合以提高定位精度。同时将定位误差在设定阈值范围内的已定位节点转化为信标节点,进行迭代协作,从而在控制误差传播的前提下增加定位覆盖。仿真结果表明,ICDV-Hop算法与传统DV-Hop算法相比,定位精度和定位覆盖均有明显改善,定位性能受网络条件影响小,表现出良好的可靠性和鲁棒性,尤其是在信标节点比例较低及网络稀疏的情况下。
Aimed at the shortage of DV-Hop localization algorithm in wireless sensor networks, an optimization algorithm based on iterative collaboration (ICDV-Hop algorithm) is proposed. By limiting the number of hops to reduce the distance error, the collinearity test is used to test the geometric positional relationship between nodes and the optimal beacon triangle is selected to improve the positioning accuracy. At the same time, the positioned nodes whose positioning error is within the set threshold are transformed into beacon nodes for iterative cooperation, so as to increase the positioning coverage under the premise of control error propagation. The simulation results show that compared with the traditional DV-Hop algorithm, the ICDV-Hop algorithm has significantly improved the positioning accuracy and positioning coverage, and the positioning performance is less affected by the network conditions and shows good reliability and robustness, especially in the letter When the ratio of target nodes is low and the network is sparse.