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A Study of Localization Accuracy Using Multiple Frequencies and Powers

机译：使用多个频率和幂的定位精度研究

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摘要

Wireless localization using the received signal strength (RSS) can have tremendous savings over using specialized positioning infrastructures. In this work, we explore improving RSS localization performance in multipath environments by varying the transmitter's signal power and frequency. We first derive and analyze the Cramér-Rao Lower Bound (CRLB) of RSS-based localization based on the frequency dependent path loss propagation model that considers the transmitter's signal power and frequency. The derived CRLB shows the feasibility of improving localization performance by applying frequency and power level selection for RSS-based localization. Using this analysis, we develop two new selection metrics based on the observed standard deviations of RSS as well as residuals. We then show a set of selection methods that attempt to select the combinations of power and frequencies which minimize the localization error in a representative class of localization algorithms. Our simulation results confirm the proposed selection methods can improve the localization accuracy under CRLB. Additionally, using active RFID tags, we experimentally characterize the effect of using multiple signal powers and frequencies on a wide spectrum of RSS-based algorithms. We found that the performance of all the algorithms improves when leveraging on multiple power levels and frequencies, although different algorithms present different sensitivity in terms of localization accuracy under different selection methods.
机译：与使用专用定位基础结构相比，使用接收信号强度（RSS）进行无线定位可以节省大量成本。在这项工作中，我们探索通过改变发射器的信号功率和频率来改善多径环境中的RSS定位性能。我们首先基于频率相关的路径损耗传播模型（考虑了发射机的信号功率和频率），推导并分析了基于RSS的Cramér-Rao下界（CRLB）。导出的CRLB显示了通过为基于RSS的定位应用频率和功率级别选择来提高定位性能的可行性。使用此分析，我们根据观察到的RSS的标准偏差以及残差开发了两个新的选择指标。然后，我们展示了一组选择方法，这些方法试图选择功率和频率的组合，以使代表性算法中的定位误差最小化。仿真结果证实了所提出的选择方法可以提高CRLB条件下的定位精度。此外，通过使用有源RFID标签，我们在各种基于RSS的算法上实验性地表征了使用多种信号功率和频率的影响。我们发现，尽管在不同的选择方法下，不同的算法在定位精度方面表现出不同的灵敏度，但在利用多个功率水平和频率时，所有算法的性能都会有所提高。

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