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Position estimation of mobile mapping imaging sensors using aerial imagery

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Mobile mapping has become an important extension to traditional geo-information acquisition techniques. Its unique ability to record street-level data using laser scanners or cameras on a large scale complements and augments the phootogrammetric portfolio. Particulary in urban areas, MM plays a significant role, as it enables compleentary data representations of the scene in conjunction with orther data-capture solutions.
In general, urban areas pose a challenge with respect to satellite-based positioning solutions due to high-rise buildings and other tall structures in built-up area which may obstruct the direct-line-of-sight to navigation satellites. As a consequence , multipath and non-line-of-sight effects may occur and impede the position estimation of the receiver.
To this end, the present reseach investigates the possibility to integrated external ground truth derived from areial images into the position estimation of the MM platform in order (1) to veryify and (2) to improve its accuracy if possible.
Aerial images are a standard product in many countries and are at regular intervals at a nationwide scale. The effects which hinder a reliable position estimation of MM platforms are not applicable to aircrafts, as the direct line-of sight to navigation satellites is usually not obstructed. Calibrated cameras, highly accurate inertial sensors, and positioning equipment enable precise sensor orientation and thus the recording of high resolution nadis as well as oblique imagery with great accuracy.
In general, this reseach investigates the use of aerial images for the correction of MM imaging data. The development of novel techniques to deal with this non-standard regritation problem is the focus or this reseach effort. The combination of image reprojection mechanics, guided matching strategis, and illumination-invariant similarity measures enable the identification of highly accurate correspondences between the aerial and the terresterial data sets at hand. Since aerial images are widely available, frequently updated, and sensor systems are becoming more powerful. presented techniques demonstrated the feasibility to overcome geometrics differences efficiently. Solving positioning issues in urban areas is not solely a research problem for terestrial mapping but also for closely related fields and technologies, such as robotics, UAV photogrammetry, or autonomous driving. The utilisation of visual cues or the correction of platform trajectories is not only a viable but also a cost-efficient and accurate metho, which may well experiences a move widespread use in the future.

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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

DS 778.35 PHI p

Penerbit

Netherland : University of Twente., 2019

Deskripsi Fisik

x, 154 hlm. : illus. ; 24 cm.

Bahasa

Inggris

ISBN/ISSN

978-90-365-4884-7

Klasifikasi

778.35

Tipe Isi

text

Tipe Media

other

Tipe Pembawa

unspecified

Edisi

-

Subjek

Foto Udara

Info Detail Spesifik

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Pernyataan Tanggungjawab

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Versi lain/terkait

Lampiran Berkas

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