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An Efficient NLOS Errors Mitigation Algorithm for TOA-Based Localization

机译:基于TOA的本地化的有效NLOS误差缓解算法

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摘要

In time-of-arrival (TOA) localization systems, errors caused by non-line-of-sight (NLOS) signal propagation could significantly degrade the location accuracy. Existing works on NLOS error mitigation commonly assume that NLOS error statistics or the TOA measurement noise variances are known. Such information is generally unavailable in practice. The goal of this paper is to develop an NLOS error mitigation scheme without requiring such information. The core of the proposed algorithm is a constrained least-squares optimization, which is converted into a semidefinite programming (SDP) problem that can be easily solved by using the CVX toolbox. This scheme is then extended for cooperative source localization. Additionally, its performance is better than existing schemes for most of the scenarios, which will be validated via extensive simulation.
机译:在到达时间(TOA)定位系统中,由非视距(NLOS)信号传播引起的错误可能会大大降低定位精度。关于NLOS误差缓解的现有工作通常假定NLOS误差统计信息或TOA测量噪声方差是已知的。此类信息通常在实践中不可用。本文的目的是开发一种不需要此类信息的NLOS错误缓解方案。所提出算法的核心是受约束的最小二乘优化,该优化被转换为可以使用CVX工具箱轻松解决的半定规划(SDP)问题。然后扩展该方案以进行协作源定位。此外,在大多数情况下,其性能均优于现有方案,这将通过广泛的仿真进行验证。

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