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Target Localization via Integrated and Segregated Ranging Based on RSS and TOA Measurements

机译:基于RSS和TOA测量的集成和隔离测量的目标定位

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摘要

This work addresses the problem of target localization in adverse non-line-of-sight (NLOS) environments by using received signal strength (RSS) and time of arrival (TOA) measurements. It is inspired by a recently published work in which authors discuss about a critical distance below and above which employing combined RSS-TOA measurements is inferior to employing RSS-only and TOA-only measurements, respectively. Here, we revise state-of-the-art estimators for the considered target localization problem and study their performance against their counterparts that employ each individual measurement exclusively. It is shown that the hybrid approach is not the best one by default. Thus, we propose a simple heuristic approach to choose the best measurement for each link, and we show that it can enhance the performance of an estimator. The new approach implicitly relies on the concept of the critical distance, but does not assume certain link parameters as given. Our simulations corroborate with findings available in the literature for line-of-sight (LOS) to a certain extent, but they indicate that more work is required for NLOS environments. Moreover, they show that the heuristic approach works well, matching or even improving the performance of the best fixed choice in all considered scenarios.
机译:这项工作通过使用接收的信号强度(RSS)和到达时间(TOA)测量来解决不利非视线(NLOS)环境中的目标定位问题。它受到最近发表的工作的启发,其中作者讨论了以下的临界距离,并且以上采用组合的RSS-TOA测量值不如采用RSS-ock和TOA的测量值。在这里,我们修改了最先进的估计,了解所考虑的目标本地化问题,并研究其对同行的表现,该对手专门使用每个单独的测量。默认情况下,混合方法不是最好的。因此,我们提出了一种简单的启发式方法来选择每个链接的最佳测量,我们表明它可以提高估计器的性能。新方法隐含地依赖于关键距离的概念,但不承担给定的某些链路参数。我们的模拟与文献中的调查结果进行了证实,在一定程度上进行了视线(LOS),但它们表明NLOS环境需要更多的工作。此外,他们表明启发式方法很好,匹配甚至提高所有所考虑的场景中最好的固定选择的性能。

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