GNSS-Aided Satellite Localization by Using Various Kalman Filters

Mert Sever; Chingiz Hajiyev

doi:10.1007/978-3-031-29933-9_27

GNSS-Aided Satellite Localization by Using Various Kalman Filters

Mert Sever^*, Chingiz Hajiyev

^*Corresponding author for this work

Department of Aeronautical Engineering

Turkish National Defence University

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

2 Citations (Scopus)

Abstract

This chapter is devoted comparison of the satellite position and velocity states estimation with the use of traditional extended, extended with linear measurements, and Newton Raphson aided extended Kalman Filters. In this study, a low-earth orbiting satellite position and velocity states are estimated by using the above filters. A global navigation satellite system (GNSS) receiver is modeled using a pseudo-range approach. Obtained results were compared and discussed. An attempt was made to determine the best method for estimating the satellite’s position. The accuracy of the estimates was shown for each estimation approach.

Original language	English
Title of host publication	Sustainable Aviation
Publisher	Springer Nature
Pages	249-260
Number of pages	12
DOIs	https://doi.org/10.1007/978-3-031-29933-9_27
Publication status	Published - 2023

Publication series

Name	Sustainable Aviation
Volume	Part F4673
ISSN (Print)	2730-7778
ISSN (Electronic)	2730-7786

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

Keywords

Kalman Filter
Satellite position estimation

Access to Document

10.1007/978-3-031-29933-9_27

Cite this

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abstract = "This chapter is devoted comparison of the satellite position and velocity states estimation with the use of traditional extended, extended with linear measurements, and Newton Raphson aided extended Kalman Filters. In this study, a low-earth orbiting satellite position and velocity states are estimated by using the above filters. A global navigation satellite system (GNSS) receiver is modeled using a pseudo-range approach. Obtained results were compared and discussed. An attempt was made to determine the best method for estimating the satellite{\textquoteright}s position. The accuracy of the estimates was shown for each estimation approach.",

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AU - Sever, Mert

AU - Hajiyev, Chingiz

PY - 2023

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AB - This chapter is devoted comparison of the satellite position and velocity states estimation with the use of traditional extended, extended with linear measurements, and Newton Raphson aided extended Kalman Filters. In this study, a low-earth orbiting satellite position and velocity states are estimated by using the above filters. A global navigation satellite system (GNSS) receiver is modeled using a pseudo-range approach. Obtained results were compared and discussed. An attempt was made to determine the best method for estimating the satellite’s position. The accuracy of the estimates was shown for each estimation approach.

KW - Kalman Filter

KW - Satellite position estimation

UR - https://www.scopus.com/pages/publications/105006810341

U2 - 10.1007/978-3-031-29933-9_27

DO - 10.1007/978-3-031-29933-9_27

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SP - 249

EP - 260

BT - Sustainable Aviation

PB - Springer Nature

ER -

GNSS-Aided Satellite Localization by Using Various Kalman Filters

Abstract

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Keywords

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