基于局部保持典型相关分析的无线传感器网络三维定位算法

3D Localization Estimation Algorithm Based on Locality Preserving Canonical Correlation Analysis in Wireless Sensor Networks

针对目前无线传感器网络三维空间定位算法精度不高、稳定性差等问题,在基于局部保持典型相关分析LPCCA模型的基础上构造三维定位算法3D-LE-LPCCA。首先,将LPCCA模型拓展到三维空间并建立信号空间和物理空间的映射模型,通过求解映射模型得到未知节点在物理空间上的临近节点集;其次,采用共面度阈值和体积比阈值的约束在临近节点集上计算出最佳定位单元;最后,采用最佳定位单元计算未知节点的坐标。仿真实验表明,该算法具有良好的定位效果,有效地提高了三维定位算法的精度和稳定性,降低了节点能耗。

Since existing three dimensional localization algorithms have the drawbacks of low positioning accuracy and poor stability,3D-LE-LPCCA algorithm was put forward. Firstly, locality preserving canonical correlation analysis is extended to three dimensional space and a mapping model between signal space and physical coordinate space is built. After solving the model, the adjacent node which is of unknown nodes in physical coordinate space is obtained. Second- ly, our algorithm calculates the best positioning unit in the adjacent node set in constrains of degree of coplanar and volume ratio. Finally, the coordinate of the unknown node is calculated through the best positioning unit. The simulation results show that 3D-LE-LPCCA algorithm has a good localization effect and improves the accuracy and stability of the three-dimensional localization algorithm, and reduces the energy consumption of the node.