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关于定位系统完整性的综合调查

A Comprehensive Survey on the Integrity of Localization Systems.

作者信息

Maharmeh Elias, Alsayed Zayed, Nashashibi Fawzi

机构信息

Valeo Mobility Tech Center (VMTC), 6 Rue Daniel Costantini, 94000 Créteil, France.

Inria-ASTRA Team, 48 Rue Barrault, 75013 Paris, France.

出版信息

Sensors (Basel). 2025 Jan 9;25(2):358. doi: 10.3390/s25020358.

DOI:10.3390/s25020358
PMID:39860728
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11768486/
Abstract

This survey extends and refines the existing definitions of integrity and protection level in localization systems (localization as a broad term, i.e., not limited to GNSS-based localization). In our definition, we study integrity from two aspects: quality and quantity. Unlike existing reviews, this survey examines integrity methods covering various localization techniques and sensors. We classify localization techniques as optimization-based, fusion-based, and SLAM-based. A new classification of integrity methods is introduced, evaluating their applications, effectiveness, and limitations. Comparative tables summarize strengths and gaps across key criteria, such as algorithms, evaluation methods, sensor data, and more. The survey presents a general probabilistic model addressing diverse error types in localization systems. Findings reveal a significant research imbalance: 73.3% of surveyed papers focus on GNSS-based methods, while only 26.7% explore non-GNSS approaches like fusion, optimization, or SLAM, with few addressing protection level calculations. Robust modeling is highlighted as a promising integrity method, combining quantification and qualification to address critical gaps. This approach offers a unified framework for improving localization system reliability and safety. This survey provides key insights for developing more robust localization systems, contributing to safer and more efficient autonomous operations.

摘要

本次调查扩展并完善了定位系统中完整性和保护级别的现有定义（定位作为一个广义术语，即不限于基于全球导航卫星系统的定位）。在我们的定义中，我们从质量和数量两个方面研究完整性。与现有综述不同，本次调查考察了涵盖各种定位技术和传感器的完整性方法。我们将定位技术分为基于优化的、基于融合的和基于同步定位与地图构建（SLAM）的。引入了一种新的完整性方法分类，评估它们的应用、有效性和局限性。比较表总结了关键标准（如算法、评估方法、传感器数据等）的优势和差距。本次调查提出了一个通用概率模型，用于解决定位系统中的各种误差类型。研究结果揭示了一个显著的研究失衡：73.3%的被调查论文关注基于全球导航卫星系统的方法，而只有26.7%探索融合、优化或同步定位与地图构建等非全球导航卫星系统方法，很少有论文涉及保护级别计算。稳健建模被强调为一种有前景的完整性方法，它结合了量化和定性来解决关键差距。这种方法为提高定位系统的可靠性和安全性提供了一个统一框架。本次调查为开发更稳健的定位系统提供了关键见解，有助于实现更安全、更高效的自主运行。

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