Various methods have been proposed for passive localization by using a network of sensors measuring different parameters such as the angle of arrival (AOA), time difference of arrival (TDOA), Doppler frequency difference of arrival (FDOA), differential received signal strength (DRSS), the gain ratio of arrival (GROA), or a combination of these pieces of information. In this paper, a method for target localization based on power of received signal in multiple stations has been proposed for two scenarios. In one scenario, the receiving antennas are omnidirectional and in the other scenario they are directional. We have derived a closed-form solution for source localization in the first scenario and we have proposed two methods (i.e., random search and Taylor series) for estimating the target location in the second scenario. Using computer simulations, the performance of our methods was compared with the Cramer–Rao lower bound (CRLB) and it was shown that the proposed scheme outperforms conventional AOA-only measurement methods. Also, the effect of estimation error of parameter $n$ (which is related to the signal propagation path-loss exponent in the environment) on the performance of the proposed method was analyzed and it was concluded that it has no significant influence on the performance of the proposed method. Finally, the performance of the proposed method has been evaluated using the real received signal strength (RSS) data.

中文翻译：

---

基于RSS的定位封闭形式解决方案

通过使用传感器网络测量不同参数，例如到达角 (AOA)、到达时间差 (TDOA)、多普勒到达频率差 (FDOA)、差分接收信号强度 (DRSS)，已经提出了各种无源定位方法。 )、到达增益比 (GROA) 或这些信息的组合。本文针对两种场景提出了一种基于多站接收信号功率的目标定位方法。在一种情况下，接收天线是全向的，而在另一种情况下，它们是定向的。我们在第一个场景中推导出了源定位的封闭形式解决方案，并且在第二个场景中我们提出了两种方法（即随机搜索和泰勒级数）来估计目标位置。使用计算机模拟，我们的方法的性能与 Cramer-Rao 下界 (CRLB) 进行了比较，结果表明所提出的方案优于传统的仅 AOA 测量方法。此外，还分析了参数$n$（与环境中信号传播路径损耗指数有关）的估计误差对所提方法性能的影响，得出的结论是它对性能没有显着影响。提出的方法。最后，使用实际接收信号强度 (RSS) 数据评估了所提出方法的性能。分析了参数$n$（与环境中信号传播路径损耗指数有关）的估计误差对所提方法性能的影响，得出的结论是它对算法的性能没有显着影响。提出的方法。最后，使用实际接收信号强度 (RSS) 数据评估了所提出方法的性能。分析了参数$n$（与环境中信号传播路径损耗指数有关）的估计误差对所提方法性能的影响，得出的结论是它对算法的性能没有显着影响。提出的方法。最后，使用实际接收信号强度 (RSS) 数据评估了所提出方法的性能。