GNSS/Inertial Navigation/Wireless Station Fusion UAV 3-D Positioning Algorithm With Urban Canyon Environment

Tang, Chengkai; Wang, Yuyang; Zhang, Lingling; Zhang, Yi

doi:10.1109/jsen.2022.3199487

Cited by 17 publications

(3 citation statements)

References 33 publications

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“…This issue was solved by using double-frequency (L1, L2) GNSS receivers on board UAVs. Consequently, at present, it is possible to rapidly acquire data characterized by centimetric accuracy by using a UAV platform without the need for GCPs and therefore without the burden of walking within hazardous areas [45][46][47][48][49][50][51]. The goal of this contribution is to present a workflow that allows us to rapidly perform an assessment of landslide dynamics even during acceleration phases.…”

Section: Introductionmentioning

confidence: 99%

Rapid Assessment of Landslide Dynamics by UAV-RTK Repeated Surveys Using Ground Targets: The Ca’ Lita Landslide (Northern Apennines, Italy)

Ciccarese,

Tondo,

Mulas

et al. 2024

Remote Sensing

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The combined use of Uncrewed Aerial Vehicles (UAVs) with an integrated Real Time Kinematic (RTK) Global Navigation Satellite System (GNSS) module and an external GNSS base station allows photogrammetric surveys with centimeter accuracy to be obtained without the use of ground control points. This greatly reduces acquisition and processing time, making it possible to perform rapid monitoring of landslides by installing permanent and clearly recognizable optical targets on the ground. In this contribution, we show the results obtained in the Ca’ Lita landslide (Northern Apennines, Italy) by performing multi-temporal RTK-aided UAV surveys. The landslide is a large-scale roto-translational rockslide evolving downslope into an earthslide–earthflow. The test area extends 60 × 103 m2 in the upper track zone, which has recently experienced two major reactivations in May 2022 and March 2023. A catastrophic event took place in May 2023, but it goes beyond the purpose of the present study. A total of eight UAV surveys were carried out from October 2020 to March 2023. A total of eight targets were installed transversally to the movement direction. The results, in the active portion of the landslide, show that between October 2020 and March 2023, the planimetric displacement of targets ranged from 0.09 m (in the lateral zone) to 71.61 m (in the central zone). The vertical displacement values ranged from −2.05 to 5.94 m, respectively. The estimated positioning errors are 0.01 (planimetric) and 0.03 m (vertical). The validation, performed by using data from a permanent GNSS receiver, shows maximum differences of 0.18 m (planimetric) and 0.21 m (vertical). These results, together with the rapidity of image acquisition and data processing, highlight the advantages of using this rapid method to follow the evolution of relatively rapid landslides such as the Ca’ Lita landslide.

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Section: Introductionmentioning

confidence: 99%

Rapid Assessment of Landslide Dynamics by UAV-RTK Repeated Surveys Using Ground Targets: The Ca’ Lita Landslide (Northern Apennines, Italy)

Ciccarese,

Tondo,

Mulas

et al. 2024

Remote Sensing

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“…The architecture is based on inertial measurement array (IMA) and GPS for data fusion, the bottom layer uses Kalman filter for data filtering, the middle layer for positioning compensation, the upper layer for final fusion positioning, to achieve the UAV positioning accuracy. In 2022, aiming at the positioning scenario of UAV in urban environment where GNSS is susceptible to interference, a multidimensional fusion positioning algorithm based on probability density was proposed [15]. Based on GNSS, IMU and wireless base station data, the algorithm fused from the perspective of probability, which reduces the complexity of the algorithm and has good positioning accuracy.…”

Section: Introductionmentioning

confidence: 99%

A regional positioning system for transformer substation based on BDS/INS/UWB

Cai,

Zhao,

Liu

et al. 2023

International Conference on Remote Sensing, Mapping, and Geographic Systems (RSMG 2023)

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Regional positioning can provide position information for objects in a certain area. In order to solve the positioning accuracy problem of regional positioning, a regional positioning system based on the integration of Inertial Navigation System (INS), Beidou System (BDS) and UWB System is proposed, so as to achieve accurate positioning in a certain area. Firstly, a multi-dimensional information fusion framework based on Extended Kalman filter (EKF), redundant information filter (RIF) and weighted fusion was proposed. In this framework, RIF_LP (Liner Prediction) algorithm and ILCTA (Information Lossless Coordinate Transformation Algorithm) are proposed. Finally, the experimental results show that the positioning fluctuation amplitude of the fusion positioning scheme is greatly reduced, and the positioning accuracy is higher than each single positioning scheme. The proposed fusion framework and algorithms have certain reference value for the construction of regional fusion positioning.

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“…As the number of satellites in orbit increases, the precision of satellite navigation has greatly improved. However, satellite navigation is susceptible to harsh environments, such as tunnels and urban canyons [2][3][4]. Cooperative vehicle infrastructure systems (CVIS) are widely applied to make up for the shortcomings of satellite positioning [5].…”

Section: Introductionmentioning

confidence: 99%

Self-Position Determination Based on Array Signal Subspace Fitting under Multipath Environments

Cao,

Li,

Tang

et al. 2023

Sensors

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A vehicle’s position can be estimated with array receiving signal data without the help of satellite navigation. However, traditional array self-position determination methods are faced with the risk of failure under multipath environments. To deal with this problem, an array signal subspace fitting method is proposed for suppressing the multipath effect. Firstly, all signal incidence angles are estimated with enhanced spatial smoothing and root multiple signal classification (Root-MUSIC). Then, non-line-of-sight (NLOS) components are distinguished from multipath signals using a K-means clustering algorithm. Finally, the signal subspace fitting (SSF) function with a P matrix is established to reduce the NLOS components in multipath signals. Meanwhile, based on the initial clustering estimation, the search area can be significantly reduced, which can lead to less computational complexity. Compared with the C-matrix, oblique projection, initial signal fitting (ISF), multiple signal classification (MUSIC) and signal subspace fitting (SSF), the simulated experiments indicate that the proposed method has better NLOS component suppression performance, less computational complexity and more accurate positioning precision. A numerical analysis shows that the complexity of the proposed method has been reduced by at least 7.64dB. A cumulative distribution function (CDF) analysis demonstrates that the estimation accuracy of the proposed method is increased by 3.10dB compared with the clustering algorithm and 11.77dB compared with MUSIC, ISF and SSF under multipath environments.

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GNSS/Inertial Navigation/Wireless Station Fusion UAV 3-D Positioning Algorithm With Urban Canyon Environment

Cited by 17 publications

References 33 publications

Rapid Assessment of Landslide Dynamics by UAV-RTK Repeated Surveys Using Ground Targets: The Ca’ Lita Landslide (Northern Apennines, Italy)

Rapid Assessment of Landslide Dynamics by UAV-RTK Repeated Surveys Using Ground Targets: The Ca’ Lita Landslide (Northern Apennines, Italy)

A regional positioning system for transformer substation based on BDS/INS/UWB

Self-Position Determination Based on Array Signal Subspace Fitting under Multipath Environments

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