Design and Implementation of the Correntropy-Based Filter for GNSS Vector Tracking and Positioning
Liu, Jian ; Kong, Qinglei ; Yin, Feng ; Cai, Zhanzhang LU
; Sun, Mengfei
and Chen, Bo
(2025)
In IEEE Transactions on Aerospace and Electronic Systems
61(5).
p.14894-14909
- Abstract
In recent decades, a significant advancement in the Global Navigation Satellite System (GNSS) has been adopting the vector tracking (VT) technique, particularly in environments where stable and reliable positioning is essential. It facilitates rapid reacquisition and continuous tracking of GNSS signals by linking the data processing and signal processing modules. In challenging environments affected by multipath and non-line-of-sight errors, such interaction adversely degrades VT’s performance by introducing non-Gaussian error propagation between the navigation processor and baseband channels. This study presents a robust filtering approach based on maximum correntropy criterion optimization to address the above challenges. A... (More)
In recent decades, a significant advancement in the Global Navigation Satellite System (GNSS) has been adopting the vector tracking (VT) technique, particularly in environments where stable and reliable positioning is essential. It facilitates rapid reacquisition and continuous tracking of GNSS signals by linking the data processing and signal processing modules. In challenging environments affected by multipath and non-line-of-sight errors, such interaction adversely degrades VT’s performance by introducing non-Gaussian error propagation between the navigation processor and baseband channels. This study presents a robust filtering approach based on maximum correntropy criterion optimization to address the above challenges. A multikernel assignment strategy has also been formulated to enhance VT stability in demanding scenarios. Extensive tests have been conducted to assess the performance and efficacy of the proposed methodology. The results indicate that the proposed filter model significantly reduces positioning errors in static and dynamic scenarios. Moreover, the method demonstrates resilience and reliability across diverse urban settings.
(Less)
- author
- Liu, Jian
; Kong, Qinglei
; Yin, Feng
; Cai, Zhanzhang
LU
; Sun, Mengfei
and Chen, Bo
- organization
- publishing date
- 2025
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Adaptive kernel, Global Navigation Satellite System (GNSS), maximum correntropy criterion (MCC), non-Gaussian errors, vector tracking (VT)
- in
- IEEE Transactions on Aerospace and Electronic Systems
- volume
- 61
- issue
- 5
- pages
- 16 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- external identifiers
-
- scopus:105012366727
- ISSN
- 0018-9251
- DOI
- 10.1109/TAES.2025.3588478
- language
- English
- LU publication?
- yes
- additional info
- Publisher Copyright: © 1965-2011 IEEE.
- id
- ad755357-2339-4e16-a031-0418c8f65875
- date added to LUP
- 2026-01-21 15:22:16
- date last changed
- 2026-01-23 11:53:32
@article{ad755357-2339-4e16-a031-0418c8f65875,
abstract = {{<p>In recent decades, a significant advancement in the Global Navigation Satellite System (GNSS) has been adopting the vector tracking (VT) technique, particularly in environments where stable and reliable positioning is essential. It facilitates rapid reacquisition and continuous tracking of GNSS signals by linking the data processing and signal processing modules. In challenging environments affected by multipath and non-line-of-sight errors, such interaction adversely degrades VT’s performance by introducing non-Gaussian error propagation between the navigation processor and baseband channels. This study presents a robust filtering approach based on maximum correntropy criterion optimization to address the above challenges. A multikernel assignment strategy has also been formulated to enhance VT stability in demanding scenarios. Extensive tests have been conducted to assess the performance and efficacy of the proposed methodology. The results indicate that the proposed filter model significantly reduces positioning errors in static and dynamic scenarios. Moreover, the method demonstrates resilience and reliability across diverse urban settings.</p>}},
author = {{Liu, Jian and Kong, Qinglei and Yin, Feng and Cai, Zhanzhang and Sun, Mengfei and Chen, Bo}},
issn = {{0018-9251}},
keywords = {{Adaptive kernel; Global Navigation Satellite System (GNSS); maximum correntropy criterion (MCC); non-Gaussian errors; vector tracking (VT)}},
language = {{eng}},
number = {{5}},
pages = {{14894--14909}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
series = {{IEEE Transactions on Aerospace and Electronic Systems}},
title = {{Design and Implementation of the Correntropy-Based Filter for GNSS Vector Tracking and Positioning}},
url = {{http://dx.doi.org/10.1109/TAES.2025.3588478}},
doi = {{10.1109/TAES.2025.3588478}},
volume = {{61}},
year = {{2025}},
}