In a wireless sensor network, the localized sensors are essential for efficient management of the network. In recent years, we have seen the implementation of various localization schemes. Few schemes presume to use mobile beacon because it has many potentialities. Despite many potentialities, the mobile beacon-based localization schemes suffer from two significant problems. First, the shorter beaconing interval increases the communication overhead and degrades the network lifetime. Second, the radio propagation irregularity minimizes the uniform coverage. For a better network lifetime, we need to reduce the communication overhead. Similarly, consistent coverage is improved through better path planning and enhanced beaconing range. However, most of the proposed geometric schemes in literature fails to address both the problems with better localization accuracy. In this paper, we address the underlying impact of shorter beaconing interval and the radio propagation irregularity. The proposed scheme utilizes the geometric least square curve fitting method for localization (GLSCFL). The results show that the proposed method provides better localization accuracy than other geometric schemes.

在无线传感器网络中，本地化传感器对于有效管理网络至关重要。近年来，我们已经看到了各种本地化方案的实施。很少有方案假定使用移动信标，因为它具有很多潜力。尽管有很多潜力，但是基于移动信标的本地化方案存在两个重大问题。首先，较短的信标间隔会增加通信开销并降低网络寿命。第二，无线电传播的不规则性使均匀覆盖范围最小。为了延长网络寿命，我们需要减少通信开销。同样，通过更好的路径规划和扩大的信标范围可以改善一致的覆盖范围。然而，文献中提出的大多数几何方案都无法以更好的定位精度解决这两个问题。在本文中，我们解决了缩短信标间隔和无线电传播不规则性的潜在影响。所提出的方案利用几何最小二乘曲线拟合方法进行定位（GLSCFL）。结果表明，与其他几何方案相比，该方法具有更好的定位精度。