Helmert transformation with mixed geodetic and Cartesian coordinates

Lin, Peng; Chang, Guobin; Gao, Jingxiang; Wang, Qianxin; Bian, Hefang

doi:10.1016/j.asr.2017.11.029

Cited by 6 publications

(6 citation statements)

References 18 publications

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“…The function model for the extrapolation estimation method based on the generalized EIV model [19,20] is as follows:…”

Section: Extrapolation Estimation Methods Based On the Generalized Eivmentioning

confidence: 99%

“…Wang et al proposed the estimation model of 3D datum transformation under a large rotation angle and arbitrary scale conditions based on the generalized EIV model [19]. Lin et al proposed the prediction model of 3D datum transformation of source coordinates in the form of geodetic coordinates based on the nonlinear Gauss-Helmert model [20].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Robust Prediction Algorithm Based on a General EIV Model for Multiframe Transformation

Yao

Lin

Gao

et al. 2019

Mathematical Problems in Engineering

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In modern geodesy, there are cases in which the target frame is unique and there is more than one source frame. Helmert transformations, which are extensively used to solve transformation parameters, can be separately solved between the target frame and one of the source frames. However, this is not globally optimal, even though each transformation is locally optimal on its own. Additionally, this also generates the problem of multiple solutions in the noncommon station of the target frame. Moreover, least squares solutions can cause estimation value distortion, with a gross error existing in observations. Thus, in this paper, Helmert transformations among three frames, that is, one target frame and two source frames, are studied as an example. A robust prediction algorithm based on the general errors-in-variables prediction algorithm and the robust estimation is derived in detail and is applied to achieve multiframe total transformation. Furthermore, simulation experiments were conducted and the results validated the superiority of the proposed total transformation method over classical separate approaches.

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“…The function model for the extrapolation estimation method based on the generalized EIV model [19,20] is as follows:…”

Section: Extrapolation Estimation Methods Based On the Generalized Eivmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Robust Prediction Algorithm Based on a General EIV Model for Multiframe Transformation

Yao

Lin

Gao

et al. 2019

Mathematical Problems in Engineering

Self Cite

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“…Coordinate transformation techniques have a wide range of applications in surveying and mapping, mechanical engineering and other fields [18,19]. The use of Helmert transform has been investigated in order to improve the coverage and density of the ground reference system [20,21]. Some scholars have suggested transforming geocentric coordinates into a closed form of geodetic and ellipsoidal coordinates, which can be applied to any point on the Earth [22,23].…”

Section: Coordinate Transformationmentioning

confidence: 99%

Bridge crack data mapping and modeling based on UAV and BIM: Towards bridge applications

Gan,

Liu,

Shi

et al. 2024

Preprint

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Traditional inspection of bridge surfaces is often inefficient and requires inspectors to inspect in high-risk areas. For the time being, Unmanned Aerial Vehicles (UAVs), as an efficient and safe means of inspection, can be equipped with high-definition cameras, and are utilised for data collection in unmanned inspections, especially in areas that are difficult for people to reach. However, how to manage the crack data obtained from UAV and machine learning recognition is still a problem. In addition, bridge modelling (BIM) based on geometric and semantic information can be applied to the inspection of bridge surfaces. To this end, this paper proposes a method for detecting and modelling bridge defects based on UAV and BIM, that is, a method for managing bridge defects by automatically identifying and locating the defect data by combining the images acquired by the UAV, which can be combined with machine vision techniques, mapping and modelling the defect data to BIM, and modelling defects from BIM as objects. Firstly, the bridge defect images captured by UAV are processed and some useful data such as coordinates are extracted from them. In this paper, a simplified coordinate method is proposed to convert the locations of the defects existing in the actual project into the coordinates in the BIM model. Meanwhile, on this basis, this paper utilises machine vision-based bridge crack detection, which is used to detect defects in the captured images and perform feature extraction on them. Finally, by modelling the identified defects, a new object with detailed information is obtained and mapped to the corresponding location in the BIM. The effectiveness of this approach is demonstrated by analysing the example of the Martyrs River Bridge. The study will be applied to combine the defects of the bridge with the BIM model, which will combine the existing state and the data from the BIM in order to perform structural inspections during the repair process.

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“…Actually, the GNSS/INS/odometer integration positioning solutions are the geodetic coordinates based on the looselycoupled processing, including the latitude, longitude and ellipsoid height in the Earth-centered frame (e-frame). However, the absolute position of the track centerline in 3D space is defined in the specific independent mapping projection coordinate frame [23]- [25]. In this section, four steps are applied for the coordinate transformation as shown in Figure 5.…”

Section: B Coordinate Transformationmentioning

confidence: 99%

Kinematic Measurement of the Railway Track Centerline Position by GNSS/INS/Odometer Integration

2019

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Accurate absolute measurement of existing lines is a task of fundamental importance to provide scientific basis for reconstruction. Traditional railway track survey methods in combination with classical geodetic surveying apparatus such as total stations cannot meet the requirements of surveying efficiency. Accurate, reliable and fast existing railway surveying applications call for an innovative method that can obtain high-precision, continuous and uniform railway track axis position in short time without interrupting the railway traffic. This paper provides an innovative solution to track axis surveying based on the integrated technique of global navigation satellite system (GNSS), inertial navigation system (INS) and odometer. GNSS/INS/odometer system does not depend on a high-precision track control network, which can operate in mobile surveying mode and significantly improve the measuring speed from 0.15 km/h to 5 km/h compared to conventional methods. Compared with satellite surveying methods, this solution for the measurement of existing line axis can obtain continuous and high-precision results in the absence of satellite signals. The results of field tests on the Zhengzhou-Xuzhou high-speed railway track show that the measurement errors are less than 0.6 cm and 1.1 cm in horizontal and vertical directions, respectively, and this measuring system is able to maintain high precision of 5 cm with a GNSS outage of 700 s, which can meet the accuracy requirements of China Specifications for Survey Engineering of High-speed Railway and serve visualization, assessment and design process of existing railways.

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Helmert transformation with mixed geodetic and Cartesian coordinates

Cited by 6 publications

References 18 publications

Robust Prediction Algorithm Based on a General EIV Model for Multiframe Transformation

Robust Prediction Algorithm Based on a General EIV Model for Multiframe Transformation

Bridge crack data mapping and modeling based on UAV and BIM: Towards bridge applications

Kinematic Measurement of the Railway Track Centerline Position by GNSS/INS/Odometer Integration

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