一种基于TOA的非视距误差优化定位算法

A TOA-based optimization positioning algorithm for non-line-of-sight errors

利用无线传感器网络进行室内定位时,信号在传播过程中难免会受到各种障碍物的干扰,即存在非视距传播。该问题一直影响了室内高精度定位的准确求解。现有的非视距误差抑制方法存在定位精度不高、鲁棒性较差等问题。为解决上述问题,文中提出了一种基于几何约束的二次规划优化方法。该方法无需获取任何测量的先验信息,在获得测距值后,采用所提出的目标函数对数据进行处理,得到被测节点的准确坐标,并对所提算法进行了详细的复杂度分析。实验结果表明,在室内恶劣的传播环境下,所提出的定位方法效果明显优于其他同类方法。

Signals in wireless sensor networks for indoor positioning are inevitably interfered by various obstacles during propagation. This phenomenon is called non-line-of-sight propagation(NLOS). Minimizing NLOS errors can help to improve the indoor positioning accuracy. However, the existing NLOS error suppression methods have some shortages such as low positioning accuracy and poor robustness. Therefore, a quadratic programming optimization method based on geometric constraints is proposed. Different from previous methods, the proposed algorithm uses the object function to process the data by the ranging value without any prior information, and obtains the accurate coordinates of the measured node. The complexity of the proposed algorithm is analyzed in detail. The experiment results show that the proposed positioning method performs better than other similar methods in the challenging indoor propagation environment.