2023
DOI: 10.1007/s10291-023-01501-w
|View full text |Cite
|
Sign up to set email alerts
|

State-space-varied moving horizon estimation for real-time PPP in the challenging low-cost antenna and chipset

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

0
2
0

Year Published

2023
2023
2023
2023

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

citations
Cited by 1 publication
(2 citation statements)
references
References 33 publications
0
2
0
Order By: Relevance
“…2) Determination of Covariance Matrix Q k−1 and R k : The computation of Q k−1 has been introduced in detail in Section III. Note that (8), (11), and (12) tell that the state estimation at the previous two steps is needed to determine the covariance matrix at the current epoch. The precedent states can be initially estimated with the WLS solutions and then gradually replaced with the EKF-based solutions.…”
Section: Filtering and Smoothing Noisy Android Raw Gnss Measurements ...mentioning
confidence: 99%
See 1 more Smart Citation
“…2) Determination of Covariance Matrix Q k−1 and R k : The computation of Q k−1 has been introduced in detail in Section III. Note that (8), (11), and (12) tell that the state estimation at the previous two steps is needed to determine the covariance matrix at the current epoch. The precedent states can be initially estimated with the WLS solutions and then gradually replaced with the EKF-based solutions.…”
Section: Filtering and Smoothing Noisy Android Raw Gnss Measurements ...mentioning
confidence: 99%
“…In the measurement domain, MHE has been applied to vehicular localization using GNSS measurements aided by map boundaries [11]. Besides, in the area of high-accuracy positioning, a state-space-varied MHE algorithm is proposed to solve inconstant states present in precise point positioning (PPP) algorithms for low-cost receivers and Android smartphones in harsh environments [12]. The prior research has focused on the design of advanced algorithms but ignores the implementation details.…”
Section: Introductionmentioning
confidence: 99%