A Fine-Tuned Positioning Algorithm for Space-Borne GNSS Timing Receivers.

GNSS LING QIAO positioning algorithm space-borne timing receiver

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
19 Apr 2020
Historique:
received: 24 12 2019
revised: 10 04 2020
accepted: 14 04 2020
entrez: 25 4 2020
pubmed: 25 4 2020
medline: 25 4 2020
Statut: epublish

Résumé

To maximize the usage of limited transmission power and wireless spectrum, more communication satellites are adopting precise space-ground beam-forming, which poses a rigorous positioning and timing requirement of the satellite. To fulfill this requirement, a space-borne global navigation satellite system (GNSS) timing receiver with a disciplined high-performance clock is preferable. The space-borne GNSS timing receiver moves with the satellite, in contrast to its stationary counterpart on ground, making it tricky in its positioning algorithm design. Despite abundant existing positioning algorithms, there is a lack of dedicated work that systematically describes the delicate aspects of a space-borne GNSS timing receiver. Based on the experimental work of the LING QIAO (NORAD ID:40136) communication satellite's GNSS receiver, we propose a fine-tuned positioning algorithm for space-borne GNSS timing receivers. Specifically, the proposed algorithm includes: (1) a filtering architecture that separates the estimation of satellite position and velocity from other unknowns, which allows for a first estimation of satellite position and velocity incorporating any variation of orbit dynamics; (2) a two-threshold robust cubature Kalman filter to counteract the adverse influence of measurement outliers on positioning quality; (3) Reynolds averaging inspired clock and frequency error estimation. Hardware emulation test results show that the proposed algorithm has a performance with a 3D positioning RMS error of 1.2 m, 3D velocity RMS error of 0.02 m/s and a pulse per second (PPS) RMS error of 11.8ns. Simulations with MATLAB show that it can effectively detect and dispose outliers, and further on outperforms other algorithms in comparison.

Identifiants

pubmed: 32325819
pii: s20082327
doi: 10.3390/s20082327
pmc: PMC7219660
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : National Natural Science Foundation of China
ID : No.61671264

Auteurs

Xi Chen (X)

National Research Institute of Information Science and Technologies, Tsinghua University, Beijing 100084, China.

QiHui Wei (Q)

National Research Institute of Information Science and Technologies, Tsinghua University, Beijing 100084, China.

YaFeng Zhan (Y)

National Research Institute of Information Science and Technologies, Tsinghua University, Beijing 100084, China.

TianYi Ma (T)

Department of Electronics Engineering, Tsinghua University, Beijing 100084, China.

Classifications MeSH