Linear Cooperative Localization Algorithm with TOA/ AOA/ AOD and Multipath

Wu, Shixun; Ren, Yi; Huang, Wenxian; Xu, Kai

doi:10.1109/wccct52091.2021.00016

Cited by 4 publications

(2 citation statements)

References 21 publications

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“…Another SAR-like approach employs AOA and FDOA to a 2-dimensional Doppler-triangulation localization method for a target that is moving in a non-linear path [94]. It has also been suggested that using TDOA and AOA from multipath returns could be sufficient to determine the position of a transmitter from a single reference point [67].…”

Section: ) Limited Sensorsmentioning

confidence: 99%

“…AOA may be employed to correct multilateration path lengths [49] and to determine the optimal beamforming for a multiple-input multiple-output (MIMO) antenna [69]. A self-localization method is proposed for cellular phones employing TOA and AOA in a multipath environment with other cooperative receivers and information from the transmitter [67]. A more algorithmic approach to localization in clutter is presented in [82].…”

Section: B Multilateration Applications 1) Clutter and Multipathmentioning

confidence: 99%

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A Review of Linear Multilateration Techniques and Applications

Widdison,

Long

2024

IEEE Access

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In multilateration, distances between an unknown location and several known points are used to determine the location of the unknown point. Papers on algorithms for multilateration, such as time of arrival (TOA), time difference of arrival (TDOA), and angle of arrival (AOA), have proliferated in the literature. These use the same equations, but are often written in a way that hides the underlying geometry and make it difficult to see the similarity in approaches between different papers. This paper provides a review of TOA and AOA-based localization approaches, with a focus on linear positioning algorithms. This paper presents simple and consistent versions of TOA, TDOA, and AOA position equations with intuitive explanations for how those equations relate to the geometry of the localization problem. This perspective can make it easier to implement these algorithms in a way that produces stable results and provides insight into the underlying geometric problem. We also review the literature relating to TDOA and AOA localization algorithms and multistatic radar.

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Section: ) Limited Sensorsmentioning

confidence: 99%

Section: B Multilateration Applications 1) Clutter and Multipathmentioning

confidence: 99%

A Review of Linear Multilateration Techniques and Applications

Widdison,

Long

2024

IEEE Access

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ML-based Approaches for Wireless NLOS Localization: Input Representations and Uncertainty Estimation

Darbinyan,

Khachatrian,

Mkrtchyan

et al. 2023

2023 IEEE Ninth International Conference on Big Data Computing Service and Applications (BigDataService)

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CSI-Embedded Cooperative Localization Method for 3D Indoor Environments

2023

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This paper introduces a novel smartphone-enabled localization technology for ambient Internet of Things (IoT) devices, leveraging the widespread use of smartphones. By utilizing the passive movement of a smartphone, we create a virtual large array that enables direct localization using only angle-of-arrival (AoA) information. Unlike traditional two-step localization methods, direct localization is unaffected by AoA estimation errors in the initial step, which are often caused by multipath channels and noise. However, direct localization methods typically require prior environmental knowledge to define the search space, with calculation time increasing as the search space expands. To address limitations in current direct localization methods, we propose a machine learning (ML)-based direct localization technique. This technique combines ML with an adaptive matching pursuit procedure, dynamically generating search spaces for precise source localization. The adaptive matching pursuit minimizes location errors despite potential accuracy fluctuations in ML across various training and testing environments. Additionally, by estimating the reflection source's location, we reduce the effects of multipath channels, enhancing localization accuracy. Extensive three-dimensional ray-tracing simulations demonstrate that our proposed method outperforms current state-of-the-art direct localization techniques in computational efficiency and operates independently of prior environmental knowledge.

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Linear Cooperative Localization Algorithm with TOA/ AOA/ AOD and Multipath

Cited by 4 publications

References 21 publications

A Review of Linear Multilateration Techniques and Applications

A Review of Linear Multilateration Techniques and Applications

ML-based Approaches for Wireless NLOS Localization: Input Representations and Uncertainty Estimation

CSI-Embedded Cooperative Localization Method for 3D Indoor Environments

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