基于禁忌搜索的无线传感器网络多源定位研究

针对无线传感器网络多源定位容易陷入局部最优的情况,提出基于禁忌搜索的多源定位方法.通过测量多个声源发出的能量建立声音能量模型,估计出模型中的声音能量和声音位置等参数,然后使用8邻域3层格点的邻域产生方式,并合理选择禁忌表长度、初始解等禁忌算法的基本参数,有效避免了多源定位易陷入局部最优的情况.将禁忌搜索算法和多分辨率搜索算法、EM算法、AMR算法进行比较,仿真结果表明,禁忌搜索能够很好地避免局部最优,且定位精度高于其他几种算法,计算复杂度相对较低.

Multi-source Localization Based on Tabu Search in Wireless Sensor Networks

To solve the problem that the multi-source localization in wireless sensor networks is easy to fall into the local optimization as a trap, a new approach to multi-source localization based on Tabu search was proposed the way on acoustic energy model was developed by measuring the signal energy received by several individual sensors, then such parameters as acoustic energy and relevant source location were estimated. To avoid falling into local optimization, the search area including 8 neighbors at 3 levels in grids was introduced, with such parameters as the length of Tabu list and initial estimation selected reasonably. Those sensors with the maximum energy received were the initial estimation nodes. Simulation results showed that in comparison with the multi-resolution (MR)search, EM algorithm and AMR algorithm, the Tabu search algorithm can avoid well falling into local optimization with higher estimating accuracy and lower computation complexity.