2021
DOI: 10.1371/journal.pone.0245561
|View full text |Cite
|
Sign up to set email alerts
|

Improving precise point positioning performance based on Prophet model

Abstract: Precision point positioning (PPP) is widely used in maritime navigation and other scenarios because it does not require a reference station. In PPP, the satellite clock bias (SCB) cannot be eliminated by differential, thus leading to an increase in positioning error. The prediction accuracy of SCB has become one of the key factors restricting positioning accuracy. Although International GNSS Service (IGS) provides the ultra-rapid ephemeris prediction part (IGU-P), its quality and real-time performance can not … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1

Citation Types

0
2
0

Year Published

2022
2022
2024
2024

Publication Types

Select...
6

Relationship

0
6

Authors

Journals

citations
Cited by 7 publications
(3 citation statements)
references
References 16 publications
0
2
0
Order By: Relevance
“…The time series chart reveals that the peak incidence of influenza in Fuzhou predominantly occurs from December to February of the following year, indicating a pronounced high-incidence pattern during the winter and spring months. In general, the influenza cases (10…”
Section: Characteristics Of Influenza Casesmentioning
confidence: 99%
See 1 more Smart Citation
“…The time series chart reveals that the peak incidence of influenza in Fuzhou predominantly occurs from December to February of the following year, indicating a pronounced high-incidence pattern during the winter and spring months. In general, the influenza cases (10…”
Section: Characteristics Of Influenza Casesmentioning
confidence: 99%
“…The SARIMA model employs time series analysis techniques to capture seasonal and temporal patterns in influenza data, incorporating considerations for seasonality, trends, and lag effects [9]. The Prophet model, developed by Facebook, is designed for time series data with both seasonality and holiday effects [10]. In contrast, the Holt-Winters model is dedicated to accounting for the seasonality and trend components within the data [11].…”
Section: Introductionmentioning
confidence: 99%
“…The Prophet model has been used to predict the satellite clock bias to improve the accuracy of precision point positioning [29]. The authors propose a hybrid method using Prophet and Long Short-Term Memory (LSTM) models to overcome the above limitations in an effort to predict accurate load.…”
Section: Prophet Algorithmmentioning
confidence: 99%