scholarly journals Kalman Filter Based PLL Robust Against Ionospheric Scintillation

10.5772/58769 ◽  
2014 ◽  
Author(s):  
Melania Susi ◽  
Marcus Andreotti ◽  
Marcio Aquino
Keyword(s):  
Kalman Filter ◽  
Ionospheric Scintillation

scholarly journals Traditional and Kalman Filter-Based GNSS Receiver Structures for Ionospheric Scintillation Monitoring and Mitigation

2021 ◽  
Author(s):  
Rafael Lopes ◽  
Felix Antreich ◽  
Hélio Kuga
Keyword(s):  
Kalman Filter ◽  
Ionospheric Scintillation ◽  
Gnss Receiver ◽  
Receiver Structures

This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible.

scholarly journals Fuzzy Logic-based Adaptive Extended Kalman Filter Algorithm for GNSS Receivers

2018 ◽  
Vol 68 (6) ◽  
pp. 560
Author(s):  
Pasumarthi Babu Sreeharsha ◽  
Venkata Ratnam Devanaboyina
Keyword(s):  
Fuzzy Logic ◽  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Global Navigation Satellite Systems ◽  
Scintillation Index ◽  
Ionospheric Scintillation ◽  
Inference System ◽  
Gnss Receivers ◽  
Ionospheric Scintillations ◽  
Adaptive Extended Kalman Filter

<p class="p1">Designing robust carrier tracking algorithms that are operable in strident environmental conditions for global navigation satellite systems (GNSS) receivers is the discern task. Major contribution in weakening the GNSS signals are ionospheric scintillations. The effect of scintillation can be known by amplitude scintillation index <em>S</em>4 and phase scintillation index sf parameters. The proposed fuzzy logic based adaptive extended Kalman filter (AEKF) method helps in modelling the signal amplitude and phase dynamically by Auto-Regressive Exogenous (ARX) analysis using Sugeno fuzzy logic inference system. The algorithm gave good performance evaluation for synthetic Cornell scintillation monitor (CSM) data and real-time strong scintillated PRN 12 L1 C/A data on October 24<span class="s1"><sup>th</sup></span>, 2012 around 21:30 h, Brazil local time collected by GNSS software navigation receiver (GSNR’x). Fuzzy logic algorithm is implemented for selecting the ARX orders based on estimated amplitude and phase ionospheric scintillation observations. Fuzzy based AEKF algorithm has the capability to mitigate ionospheric scintillations under both geomagnetic quiet and disturbed conditions.</p>

scholarly journals Performance assessment of a low-complexity autoregressive Kalman filter for GNSS carrier tracking using real scintillation time series

GPS Solutions ◽  
2021 ◽  
Vol 26 (1) ◽  
Author(s):  
Sergi Locubiche-Serra ◽  
Gonzalo Seco-Granados ◽  
José A. López-Salcedo
Keyword(s):  
Kalman Filter ◽  
A Priori ◽  
Gaussian Function ◽  
Real Data ◽  
Autoregressive Process ◽  
Low Complexity ◽  
Global Navigation Satellite Systems ◽  
Ionospheric Scintillation ◽  
Satellite Systems ◽  
Phase Dynamics

AbstractIonospheric scintillation is one of the most challenging sources of errors in global navigation satellite systems (GNSS). It is an effect of space weather that introduces rapid amplitude and phase fluctuations to transionospheric signals and, as a result, it severely degrades the tracking performance of receivers, particularly carrier tracking. It can occur anywhere on the earth during intense solar activity, but the problem aggravates in equatorial and high-latitude regions, thus posing serious concerns to the widespread deployment of GNSS in those areas. One of the most promising approaches to address this problem is the use of Kalman filter-based techniques at the carrier tracking level, incorporating some a priori knowledge about the statistics of the scintillation to be dealt with. These techniques aim at dissociating the carrier phase dynamics of interest from phase scintillation by modeling the latter through some correlated Gaussian function, such as the case of autoregressive processes. However, besides the fact that the optimality of these techniques is still to be reached, their applicability for dealing with scintillation in real-world environments also remains to be confirmed. We carry out an extensive analysis and experimentation campaign on the suitability of these techniques by processing real data captures of scintillation at low and high latitudes. We first evaluate how well phase scintillation can be modeled through an autoregressive process. Then, we propose a novel adaptive, low-complexity autoregressive Kalman filter intended to facilitate the implementation of the approach in practice. Last, we provide an analysis of the operational region of the proposed technique and the limits at which a performance gain over conventional tracking architectures is obtained. The results validate the excellence of the proposed approach for GNSS carrier tracking under scintillation conditions.

scholarly journals Tuning a Kalman filter carrier tracking algorithm in the presence of ionospheric scintillation

GPS Solutions ◽  
2017 ◽  
Vol 21 (3) ◽  
pp. 1149-1160 ◽  
Author(s):  
Melania Susi ◽  
Marcus Andreotti ◽  
Marcio Aquino ◽  
Alan Dodson
Keyword(s):  
Kalman Filter ◽  
Tracking Algorithm ◽  
Ionospheric Scintillation

scholarly journals Traditional and Kalman Filter-Based GNSS Receiver Structures for Ionospheric Scintillation Monitoring and Mitigation

2021 ◽  
Author(s):  
Rafael Lopes ◽  
Felix Antreich ◽  
Hélio Kuga
Keyword(s):  
Kalman Filter ◽  
Ionospheric Scintillation ◽  
Gnss Receiver ◽  
Receiver Structures

This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible.

Sign in / Sign up

Export Citation Format

Share Document