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

^*Bu çalışma için yazışmadan sorumlu yazar

Uçak Mühendisliği Bölümü

Turkish National Defence University

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Bölüm › bilirkişi

3 Atıf (Scopus)

Özet

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.

Orijinal dil	İngilizce
Ana bilgisayar yayını başlığı	Sustainable Aviation
Yayınlayan	Springer Nature
Sayfalar	249-260
Sayfa sayısı	12
DOI'lar	https://doi.org/10.1007/978-3-031-29933-9_27
Yayın durumu	Yayınlandı - 2023

Yayın serisi

Adı	Sustainable Aviation
Hacim	Part F4673
ISSN (Basılı)	2730-7778
ISSN (Elektronik)	2730-7786

Bibliyografik not

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

Belgeye Erişim

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

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

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title = "GNSS-Aided Satellite Localization by Using Various Kalman Filters",

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.",

keywords = "Kalman Filter, Satellite position estimation",

author = "Mert Sever and Chingiz Hajiyev",

note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.",

year = "2023",

doi = "10.1007/978-3-031-29933-9\_27",

language = "English",

series = "Sustainable Aviation",

publisher = "Springer Nature",

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TY - CHAP

T1 - GNSS-Aided Satellite Localization by Using Various Kalman Filters

AU - Sever, Mert

AU - Hajiyev, Chingiz

PY - 2023

Y1 - 2023

N2 - 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.

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

M3 - Chapter

AN - SCOPUS:105006810341

T3 - Sustainable Aviation

SP - 249

EP - 260

BT - Sustainable Aviation

PB - Springer Nature

ER -

GNSS-Aided Satellite Localization by Using Various Kalman Filters

Özet

Yayın serisi

Bibliyografik not

Belgeye Erişim

Diğer Dosyalar ve Linkler

Parmak izi

Alıntı Yap