Three Passive TDOA-AOA Receivers Based Flying-UAV Positioning in Extreme Environments

Chen, Xu; Wang, Zao; Wang, Yuhao; Wang, Zhenghai; Yu, Lisu

doi:10.1109/jsen.2020.2988920

Cited by 44 publications

(29 citation statements)

References 26 publications

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“…In summarize, to locate the target device two angles between the fixed stations' direction to the target with the North Pole and one range measurement between the stations are needed. When very simply the distance between the two displays can be measured [38]- [40].…”

Section: Angle Based Methods (Angulation)mentioning

confidence: 99%

A Comprehensive Review of Indoor/Outdoor Localization Solutions in IoT era: Research Challenges and Future Perspectives

Asaad¹,

Maghdid²

2021

Preprint

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<p>The number of connected mobile devices and Internet of Things (IoT) is growing around us, rapidly. Since, most of the people daily activities are relying on these connected things or devices. Specifically, this past year (with COVID-19) changed daily life in abroad and this is increased the use of IoT enabled technologies in health sector, work, and play. Further, the most common service via using these technologies is the localization/positioning service for different applications including: geo-tagging, billing, contact tracing, health-care system, point-of-interest recommendations, social networking, security, and more. Despite the availability of a large number of localization solutions in the literature, the precision of localization cannot meet the needs of consumers. For that reason, this paper provides an in-depth investigation of the existing technologies and techniques in the localization field, within the IoT era. Furthermore, the benefits and drawbacks of each technique with enabled technologies are illustrated and a comparison between the utilized technologies in the localization is made. The paper as a guideline is also going through all of the metrics that may be used to assess the localization solutions. Finally, the state-of-the-art solutions are examined, with challenges and perspectives regarding indoors/outdoors environments are demonstrated.</p>

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Section: Angle Based Methods (Angulation)mentioning

confidence: 99%

A Comprehensive Review of Indoor/Outdoor Localization Solutions in IoT era: Research Challenges and Future Perspectives

Asaad¹,

Maghdid²

2021

Preprint

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“…We begin the first iteration with a weight matrix C(1) as the identity matrix [31]. Based on Equation (15), with (i + 1) measurement data obtained from radio frequency signal of the additional base stations, the hybrid TDOA/AOA localization equation can be rewritten as follow:…”

Section: Optimal Solution Using Ir-rls Schemementioning

confidence: 99%

“…Zhang applied the extended Kalman filter estimator to observe the state of a mobile by linearizing measurement equations. To locate the unmanned aerial vehicle (UAV) avoiding the nonline-of-sight (NLOS) bias error, Xu [ 15 ] proposed an efficient method using only three passive RF receivers. After decomposing the NLOS link into two line-of-sight (LOS) paths, the UAV position was estimated using the position of one-bounce scatters.…”

Section: Introductionmentioning

confidence: 99%

Iterative Regression Based Hybrid Localization for Wireless Sensor Networks

Lee

Kim

You

2021

Sensors

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Among various localization methods, a localization method that uses a radio frequency signal-based wireless sensor network has been widely applied due to its robustness against noise factors and few limits on installation location. In this paper, we focus on an iterative localization scheme for a mobile with a limited number of time difference of arrival (TDOA) and angle of arrival (AOA) data measured from base stations. To acquire the optimal location of a mobile, we propose a recursive solution for localization using an iteratively reweighted-recursive least squares (IR-RLS) algorithm. The proposed IR-RLS scheme can obtain the optimal solution with a fast computational speed when additional TDOA and/or AOA data is measured from base stations. Moreover, while the number of measured TDOA/AOA data was limited, the proposed IR-RLS scheme could obtain the precise location of a mobile. The performance of the proposed IR-RLS method is confirmed through some simulation results.

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“…Step 06: Calculate the elements of the model (DLs, aods, and aoas) Stop In recent studies [55,56], more accurate localisation techniques have been introduced; however, they all are designed to work on the BSs and therefore are not comparable to our study. As the test results shown in Figure 8 reveal, ACE satisfied the new FCC rules under all conditions of k. One of the best-known features of the CORDIC algorithm is the computational efficiency it provides while imitating trigonometric functions.…”

Section: Startmentioning

confidence: 99%

Fast hardware-oriented algorithm for 3D positioning in line-of-sight and single bounced non-line-of-sight environments

Yagli¹,

Özen²,

Akkeleş³

2021

Turk J Elec Eng & Comp Sci

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The ability to find the location of a mobile object and track it in two-dimensional (2D) and three-dimensional (3D) space is an indispensable feature of wireless communication systems. In particular, the increase in demand for selfnavigation technology for use in unmanned vehicles is attracting additional attention to this area of research. The methods and techniques developed for these systems compete in terms of simplicity, performance, and accuracy. However, the majority of solutions focus on only one of these performance metrics and are not applicable to the projected systems. In this study, a new location estimation solution that satisfies all three performance metrics (simplicity, accuracy, and efficiency) is achieved. The developed algorithms can be executed on a mobile object to allow it to learn its position in space. Furthermore, the simplicity of the mathematical operations used, namely binary shift and add operations, makes our algorithm hardware-friendly. Accelerated coordinate rotation digital computer (CORDIC) algorithms are used for the first time with line-of-sight (LOS) and single-bounced-scattering non-line-of-sight (SBS NLOS) signal arriving approaches for mobile object self-positioning. This study also introduces a newly developed 'vector-breaking' method (VBM) to estimate the location of a mobile object using the arriving signals from scatters with unknown locations. Test results using the developed algorithm show that the projected level of accuracy has been achieved. Furthermore, the developed algorithm performs better than the solutions currently available in the field.

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Three Passive TDOA-AOA Receivers Based Flying-UAV Positioning in Extreme Environments

Cited by 44 publications

References 26 publications

A Comprehensive Review of Indoor/Outdoor Localization Solutions in IoT era: Research Challenges and Future Perspectives

A Comprehensive Review of Indoor/Outdoor Localization Solutions in IoT era: Research Challenges and Future Perspectives

Iterative Regression Based Hybrid Localization for Wireless Sensor Networks

Fast hardware-oriented algorithm for 3D positioning in line-of-sight and single bounced non-line-of-sight environments

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