Localization is one of the most important aspects of wireless sensor networks. Most of the localization algorithms proposed in the literature, work for static networks. However, the performance of these protocols in the mobile environment still needs to be investigated. Localization in a mobile environment may pose challenges of accuracy and computational complexity due to mobility of the nodes. In this article, we have proposed an algorithm for localization in mobile wireless sensor networks using drones (LMWSND). A drone-based algorithm is proposed to simulate the moving trajectory of the drones. The proposed drone-based algorithm uses the technique of received signal strength between the drone and unknown sensor nodes to find the distance between them. The distance thus obtained is used for localization of the unknown nodes. A new method is used to solve the system of distance equations to restrict the propagation of error. Furthermore, the mathematical analysis of the propagation error in LMWSND proves the superiority of our proposed algorithm in comparison to other algorithms. The results obtained through simulations further strengthen our conclusion that the proposed algorithm reduces the propagation of error. We have also proposed another algorithm to choose the nearby beacon points for better utilization of the network resources and to reduce the computational efforts.

中文翻译：

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使用无人机在移动无线传感器网络中进行定位

定位是无线传感器网络最重要的方面之一。文献中提出的大多数定位算法都适用于静态网络。然而，这些协议在移动环境中的性能仍有待研究。由于节点的移动性，移动环境中的定位可能会带来准确性和计算复杂性的挑战。在本文中，我们提出了一种使用无人机（LMWSND）在移动无线传感器网络中进行定位的算法。提出了一种基于无人机的算法来模拟无人机的运动轨迹。所提出的基于无人机的算法使用无人机和未知传感器节点之间的接收信号强度技术来找到它们之间的距离。如此获得的距离用于未知节点的定位。一种新的方法用于求解距离方程组以限制误差的传播。此外，LMWSND中传播误差的数学分析证明了我们提出的算法与其他算法相比的优越性。通过模拟获得的结果进一步加强了我们的结论，即所提出的算法减少了误差的传播。我们还提出了另一种算法来选择附近的信标点，以更好地利用网络资源并减少计算量。通过模拟获得的结果进一步加强了我们的结论，即所提出的算法减少了误差的传播。我们还提出了另一种算法来选择附近的信标点，以更好地利用网络资源并减少计算量。通过模拟获得的结果进一步加强了我们的结论，即所提出的算法减少了误差的传播。我们还提出了另一种算法来选择附近的信标点，以更好地利用网络资源并减少计算量。