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Title: A new path planning algorithm using a GNSS localization error map for UAVs in an urban area
Authors: Zhang, G 
Hsu, LT 
Keywords: GPS
Urban canyon
Path planning
Issue Date: Apr-2019
Publisher: Springer
Source: Journal of intelligent & robotic systems, Apr. 2019, v. 94, no. 1, p. 219-235 How to cite?
Journal: Journal of intelligent & robotic systems 
Abstract: The mission of future parcel delivery will be performed by unmanned aerial vehicles (UAVs). However, the localization of global navigation satellite systems (GNSS) in urban areas experiences the notorious multipath effect and non-line-of-sight (NLOS) reception which could potentially generate approximately 50 meters of positioning error. This misleading localization result can be hazardous for UAV applications in GNSS-challenged areas. Due to multipath complexity, there is no general solution to eliminate this effect. A solution to guide UAV operation is to plan an optimal route that smartly avoids the area with a strong multipath effect. To achieve this goal, the impact of the multipath effect in terms of positioning error at different locations must be predicted. This paper proposes to simulate the reflection route by a ray-tracing technique, aided by predicted satellite positions and the widely available 3D building model. Thus, the multipath effect in the pseudorange domain can be simulated using the reflection route and multipath noise envelope according, according to specific correlator designs. By constructing the multipath-biased pseudorange domain, the predicted positioning error can be obtained using a least square positioning method. Finally, the predicted GNSS error distribution of a target area can be further constructed. A new A* path planning algorithm is developed to combine with the GNSS error distribution. This paper designs a new cost function to consider both the distance to the destination and the positioning error at each grid. By comparing the conventional and the proposed path planning algorithms, the planned paths of the proposed methods experienced fewer positioning errors, which can lead to safer routes for UAVs in urban areas.
ISSN: 0921-0296
EISSN: 1573-0409
DOI: 10.1007/s10846-018-0894-5
Rights: ©Springer Nature B.V. 2018
This is a post-peer-review, pre-copyedit version of an article published in Journal of Intelligent & Robotic System. The final authenticated version is available online at:
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