Energy-based localization has received great interest due to its low cost and simple implementation. It is well-known that sensor placement around the source plays a significant role in localization performance. This paper considers source localization based on the received signal strength difference (RSSD). Then, we propose two methods for sensor placement using maximization of the determinant of Fisher information matrix (FIM). The first one is based on the Gradient optimization method in which our optimization metric is a function of angular locations of all sensors, and the output of this method is optimal angular sensor separation which is called the optimal angular placement (OAP). In the second approach, we obtain the optimization metric as a function of single variable for each sensor in which the sensors are arranged in step-by-step manner, this method is called sequential sensor placement (SSP) in our study. At the end of this paper, simulation results reveal the ability of the proposed sensor placements.

基于能量的本地化由于其低成本和易于实现而引起了极大的兴趣。众所周知，传感器在光源周围的放置在定位性能中起着重要作用。本文考虑基于接收信号强度差（RSSD）的源定位。然后，我们提出了两种使用费舍尔信息矩阵（FIM）行列式最大化的传感器放置方法。第一个基于梯度优化方法，其中我们的优化指标是所有传感器的角位置的函数，该方法的输出是最佳角度传感器间距，称为最佳角度放置（OAP）。在第二种方法中 我们获得了针对每个传感器的单个变量函数的优化度量，其中传感器以逐步方式进行布置，该方法在我们的研究中称为顺序传感器放置（SSP）。在本文的最后，仿真结果揭示了所提出的传感器放置的能力。