A Novel GPS Based Real Time Orbit Determination Using Adaptive Extended Kalman Filter

Yang XIAO; Limin LI; Jiachao CHANG; Kang WU; Guang LIANG; Jinpei YU

doi:10.1587/transfun.E101.A.287

A Novel GPS Based Real Time Orbit Determination Using Adaptive Extended Kalman Filter

Yang XIAO, Limin LI, Jiachao CHANG, Kang WU, Guang LIANG, Jinpei YU

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The combination of GPS measurements with the dynamic model via a Kalman filter or an extended Kalman filter, also known as GPS based reduced dynamic orbit determination (RDOD) techniques, have been widely used for accurate and real time navigation of satellites in low earth orbit (LEO). In previous studies, the GPS measurement noise variance is empirically taken as a constant, which is not reasonable because of insufficient prior information or dynamic environment. An improper estimate of the measurement noise may lead to poor performance or even divergence of the filter. In this letter, an adaptive extended Kalman filter (AEKF)-based approach using GPS dual-frequency pseudo-range measurements is presented, where the GPS pseudo-range measurement noise variance is adaptively estimated by the Carrier to Noise Ratio (C/N₀) from the tracking loop of GPS receiver. The simulation results show that the proposed AEKF approach can achieve apparent improvements of the position accuracy and almost brings no extra computational burdens for satellite borne processor.

Publication: IEICE TRANSACTIONS on Fundamentals Vol.E101-A No.1 pp.287-292

Publication Date: 2018/01/01

Publicized

Online ISSN: 1745-1337

DOI: 10.1587/transfun.E101.A.287

Type of Manuscript: LETTER

Category: Communication Theory and Signals

Authors

Yang XIAO
  Chinese Academy of Sciences,University of Chinese Academy of Sciences
Limin LI
  Wenzhou University
Jiachao CHANG
  Chinese Academy of Sciences,University of Chinese Academy of Sciences
Kang WU
  Chinese Academy of Sciences
Guang LIANG
  Chinese Academy of Sciences
Jinpei YU
  Chinese Academy of Sciences

Keyword

reduced dynamic orbit determination (RDOD), measurement noise, carrier to noise ratio (C/N₀), adaptive extended Kalman filter (AEKF)

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Yang XIAO, Limin LI, Jiachao CHANG, Kang WU, Guang LIANG, Jinpei YU, "A Novel GPS Based Real Time Orbit Determination Using Adaptive Extended Kalman Filter" in IEICE TRANSACTIONS on Fundamentals, vol. E101-A, no. 1, pp. 287-292, January 2018, doi: 10.1587/transfun.E101.A.287.
Abstract: The combination of GPS measurements with the dynamic model via a Kalman filter or an extended Kalman filter, also known as GPS based reduced dynamic orbit determination (RDOD) techniques, have been widely used for accurate and real time navigation of satellites in low earth orbit (LEO). In previous studies, the GPS measurement noise variance is empirically taken as a constant, which is not reasonable because of insufficient prior information or dynamic environment. An improper estimate of the measurement noise may lead to poor performance or even divergence of the filter. In this letter, an adaptive extended Kalman filter (AEKF)-based approach using GPS dual-frequency pseudo-range measurements is presented, where the GPS pseudo-range measurement noise variance is adaptively estimated by the Carrier to Noise Ratio (C/N₀) from the tracking loop of GPS receiver. The simulation results show that the proposed AEKF approach can achieve apparent improvements of the position accuracy and almost brings no extra computational burdens for satellite borne processor.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E101.A.287/_p

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@ARTICLE{e101-a_1_287,
author={Yang XIAO, Limin LI, Jiachao CHANG, Kang WU, Guang LIANG, Jinpei YU, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={A Novel GPS Based Real Time Orbit Determination Using Adaptive Extended Kalman Filter},
year={2018},
volume={E101-A},
number={1},
pages={287-292},
abstract={The combination of GPS measurements with the dynamic model via a Kalman filter or an extended Kalman filter, also known as GPS based reduced dynamic orbit determination (RDOD) techniques, have been widely used for accurate and real time navigation of satellites in low earth orbit (LEO). In previous studies, the GPS measurement noise variance is empirically taken as a constant, which is not reasonable because of insufficient prior information or dynamic environment. An improper estimate of the measurement noise may lead to poor performance or even divergence of the filter. In this letter, an adaptive extended Kalman filter (AEKF)-based approach using GPS dual-frequency pseudo-range measurements is presented, where the GPS pseudo-range measurement noise variance is adaptively estimated by the Carrier to Noise Ratio (C/N₀) from the tracking loop of GPS receiver. The simulation results show that the proposed AEKF approach can achieve apparent improvements of the position accuracy and almost brings no extra computational burdens for satellite borne processor.},
keywords={},
doi={10.1587/transfun.E101.A.287},
ISSN={1745-1337},
month={January},}

Copy

TY - JOUR
TI - A Novel GPS Based Real Time Orbit Determination Using Adaptive Extended Kalman Filter
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 287
EP - 292
AU - Yang XIAO
AU - Limin LI
AU - Jiachao CHANG
AU - Kang WU
AU - Guang LIANG
AU - Jinpei YU
PY - 2018
DO - 10.1587/transfun.E101.A.287
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E101-A
IS - 1
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - January 2018
AB - The combination of GPS measurements with the dynamic model via a Kalman filter or an extended Kalman filter, also known as GPS based reduced dynamic orbit determination (RDOD) techniques, have been widely used for accurate and real time navigation of satellites in low earth orbit (LEO). In previous studies, the GPS measurement noise variance is empirically taken as a constant, which is not reasonable because of insufficient prior information or dynamic environment. An improper estimate of the measurement noise may lead to poor performance or even divergence of the filter. In this letter, an adaptive extended Kalman filter (AEKF)-based approach using GPS dual-frequency pseudo-range measurements is presented, where the GPS pseudo-range measurement noise variance is adaptively estimated by the Carrier to Noise Ratio (C/N₀) from the tracking loop of GPS receiver. The simulation results show that the proposed AEKF approach can achieve apparent improvements of the position accuracy and almost brings no extra computational burdens for satellite borne processor.
ER -