基于多面体质心算法的水下传感器网络定位

Underwater Sensor Networks Localization Based on Polyhedron Centroid Algorithm

为了克服基于测距的水下定位算法以及距离无关的水下定位算法定位精度的不足,通过网络密度自适应、迭代定位和重定位、周期性更新和预测等优化措施,提出了一种距离无关的多面体质心算法,并利用仿真实验证明了多面体质心算法的定位性能明显优于ALS算法,它能够大幅度提高定位精确度,并降低定位成本。最后指出了未来水下定位算法研究应注意的问题和发展趋势。

In order to overcome the poor localization accuracy of both distance-based underwater localization algorithm and distance-independent underwater localization algorithm at present,this paper proposed a distance-independent polyhedron centroid algorithm with the optimization measures of adaptive network density,iterative location and relocation,periodically updating and forecasting,and simulation results show that not only the performance of polyhedron centroid localization algorithm is much better than ALS algorithm,and the localization accuracy can be significantly improved,but also this new localization algorithm reduces localization costs.Finally,it pointed out future research issues and trends of underwater localization algorithm.