Metaheuristic-based stochastic models for GNSS relative positioning planning-Reference-Cited by-同舟云学术

Metaheuristic-based stochastic models for GNSS relative positioning planning

Published:2023-10-29 Issue:1 Volume:28 Page:
ISSN:1080-5370
Container-title:GPS Solutions
language:en
Short-container-title:GPS Solut

Author:

Koch Ismael Érique,Klein Ivandro,Gonzaga Luiz,Rofatto Vinicius Francisco,Matsuoka Marcelo Tomio,Monico João Francisco Galera,Veronez Maurício Roberto

Funder

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Publisher

Springer Science and Business Media LLC

Subject

General Earth and Planetary Sciences

Link

https://link.springer.com/content/pdf/10.1007/s10291-023-01562-x.pdf

Reference22 articles.

1. Dogan B, Ölmez T (2015) A new metaheuristic for numerical function optimization: vortex search algorithm. Inf Sci 293(125–145):S0020025514008585. https://doi.org/10.1016/j.ins.2014.08.053

2. Eckl M, Snay R, Soler T (2001) Accuracy of GPS-derived relative positions as a function of interstation distance and observing-session duration. J Geodesy 75:633–640. https://doi.org/10.1007/s001900100204

3. El-Rabbany A (1994) The effect of physical correlations on the ambiguity resolution and accuracy estimation in GPS differential positioning. Ph.D. Thesis, University of New Brunswick, Department of Geodesy and Geomatics Engineering, Fredericton, NB

4. Erdogan B, Dogan AH (2019) Scaling of the variance covariance matrix obtained from Bernese software. Acta Geod Geoph 54:197–211. https://doi.org/10.1007/s40328-019-00252-w

5. Firuzabadì D, King RW (2012) GPS precision as a function of session duration and reference frame using multi-point software. GPS Solutions 16:191–196. https://doi.org/10.1007/s10291-011-0218-8