School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 100048, China.
School of Automation, Beijing Institute of Technology, Beijing 100081, China.
Sensors (Basel). 2019 Oct 27;19(21):4665. doi: 10.3390/s19214665.
Reliable and accurate localization of objects is essential for many applications in wireless networks. Especially for large-scale wireless sensor networks (WSNs), both low cost and high accuracy are targets of the localization technology. However, some range-free methods cannot be combined with a cooperative method, because these range-free methods are characterized by low accuracy of distance estimation. To solve this problem, we propose a hard decision-based cooperative localization method. For distance estimation, an exponential distance calibration formula is derived to estimate distance. In the cooperative phase, the cooperative method is optimized by outlier constraints from neighboring anchors. Simulations are conducted to verify the effectiveness of the proposed method. The results show that localization accuracy is improved in different scenarios, while high node density or anchor density contributes to the localization. For large-scale WSNs, the hard decision-based cooperative localization is proved to be effective.
对象的可靠和精确定位对于无线网络中的许多应用至关重要。特别是对于大规模无线传感器网络 (WSN)，低成本和高精度都是定位技术的目标。然而，一些无距离的方法不能与协作方法相结合，因为这些无距离的方法的特点是距离估计精度低。为了解决这个问题，我们提出了一种基于硬判决的协作定位方法。对于距离估计，推导了一个指数距离校准公式来估计距离。在协作阶段，通过来自相邻锚点的异常值约束来优化协作方法。进行了模拟以验证所提出方法的有效性。结果表明，在不同场景下，定位精度都得到了提高，而高节点密度或锚密度有助于定位。对于大规模 WSN，基于硬判决的协作定位被证明是有效的。
