Parallelized Processing in Kinematic Positioning for Single Frequency GNSS Receiver

Author(s):  
Hiroyuki Hatano ◽  
Atsushi Ito
Author(s):  
M. Rehak ◽  
J. Skaloud

Mapping with Micro Aerial Vehicles (MAVs whose weight does not exceed 5&amp;thinsp;kg) is gaining importance in applications such as corridor mapping, road and pipeline inspections, or mapping of large areas with homogeneous surface structure, e.g. forest or agricultural fields. In these challenging scenarios, integrated sensor orientation (ISO) improves effectiveness and accuracy. Furthermore, in block geometry configurations, this mode of operation allows mapping without ground control points (GCPs). Accurate camera positions are traditionally determined by carrier-phase GNSS (Global Navigation Satellite System) positioning. However, such mode of positioning has strong requirements on receiver’s and antenna’s performance. In this article, we present a mapping project in which we employ a single-frequency, low-cost (<&amp;thinsp;$100) GNSS receiver on a MAV. The performance of the low-cost receiver is assessed by comparing its trajectory with a reference trajectory obtained by a survey-grade, multi-frequency GNSS receiver. In addition, the camera positions derived from these two trajectories are used as observations in bundle adjustment (BA) projects and mapping accuracy is evaluated at check points (ChP). Several BA scenarios are considered with absolute and relative aerial position control. Additionally, the presented experiments show the possibility of BA to determine a camera-antenna spatial offset, so-called lever-arm.


2019 ◽  
Vol 57 (2) ◽  
pp. 881-892 ◽  
Author(s):  
Chuanbao Zhao ◽  
Yunbin Yuan ◽  
Baocheng Zhang ◽  
Min Li

2019 ◽  
Vol 10 (1) ◽  
pp. 15-20 ◽  
Author(s):  
A. P. Aleshkin ◽  
T. O. Myslivtsev ◽  
S. V. Nikiforov ◽  
P. V. Savochkin ◽  
I. V. Sakhno ◽  
...  

2015 ◽  
Vol 901 (7) ◽  
pp. 2-7
Author(s):  
A.P. Karpik ◽  
◽  
I.G. Ganagina ◽  
N.S. Kosarev ◽  
D.N. Goldobin ◽  
...  

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7265
Author(s):  
Zhitao Lyu ◽  
Yang Gao

High-precision positioning with low-cost global navigation satellite systems (GNSS) in urban environments remains a significant challenge due to the significant multipath effects, non-line-of-sight (NLOS) errors, as well as poor satellite visibility and geometry. A GNSS system is typically implemented with a least-square (LS) or a Kalman-filter (KF) estimator, and a proper weight scheme is vital for achieving reliable navigation solutions. The traditional weight schemes are based on the signal-in-space ranging errors (SISRE), elevation and C/N0 values, which would be less effective in urban environments since the observation quality cannot be fully manifested by those values. In this paper, we propose a new multi-feature support vector machine (SVM) signal classifier-based weight scheme for GNSS measurements to improve the kinematic GNSS positioning accuracy in urban environments. The proposed new weight scheme is based on the identification of important features in GNSS data in urban environments and intelligent classification of line-of-sight (LOS) and NLOS signals. To validate the performance of the newly proposed weight scheme, we have implemented it into a real-time single-frequency precise point positioning (SFPPP) system. The dynamic vehicle-based tests with a low-cost single-frequency u-blox M8T GNSS receiver demonstrate that the positioning accuracy using the new weight scheme outperforms the traditional C/N0 based weight model by 65.4% and 85.0% in the horizontal and up direction, and most position error spikes at overcrossing and short tunnels can be eliminated by the new weight scheme compared to the traditional method. It also surpasses the built-in satellite-based augmentation systems (SBAS) solutions of the u-blox M8T and is even better than the built-in real-time-kinematic (RTK) solutions of multi-frequency receivers like the u-blox F9P and Trimble BD982.


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