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Maximum Correntropy Criterion for Robust TOA-Based Localization in NLOS Environments

机译:NLOS环境中基于强大的TOA定位的最大校正标准

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摘要

We investigate the problem of time-of-arrival (TOA)-based localization under possible non-line-of-sight (NLOS) propagation conditions. To robustify the squared-range-based location estimator, we follow the maximum correntropy criterion, essentially the Welsch M-estimator with a redescending influence function which behaves like l(0)-minimization toward the grossly biased measurements, to derive the formulation. The half-quadratic technique is then applied to settle the resulting optimization problem in an alternating maximization (AM) manner. By construction, the major computational challenge at each AM iteration boils down to handling an easily solvable generalized trust region subproblem. It is worth noting that the implementation of our localization method requires nothing but merely the TOA-based range measurements and sensor positions as prior information. Simulation and experimental results demonstrate the competence of the presented scheme in outperforming several state-of-the-art approaches in terms of positioning accuracy, especially in scenarios, where the percentage of NLOS paths is not large enough.
机译:我们在可能的非视线(NLOS)传播条件下,调查到达时间(TOA)的定位问题。为了强调基于平方范围的位置估计器,我们遵循最大的正管内标准,基本上是诸如重新介绍的影响功能的绒毛估计器,其表现得像l(0) - 朝向严重偏置的测量结果,以导出制剂。然后应用半二次技术以在交替的最大化(AM)方式中沉降得到的优化问题。通过施工,每个AM迭代的主要计算挑战归结为处理易于解决的广义信任区域子问题。值得注意的是,我们的本地化方法的实现只需要基于TOA的范围测量和传感器位置作为先前信息。模拟和实验结果表明,在定位准确性方面表明了所提出的方案的能力,特别是在定位准确性方面,特别是在场景中,NLOS路径的百分比不够大。

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