Kalman filter-based architecture for robust and high-sensitivity tracking in GNSS receivers

Cycle slips strongly impact the performance of phase tracking algorithm leading, in the worst case, to a permanent loss of lock of the signal. In this paper, we propose a new nonlinear phase estimator to obtain more robust tracks. The latter stems from a Variational Bayes (VB) approximation used within the optimal Bayesian filtering formulation in case of highorder phase dynamics. A comparison with a more conventional technique, namely a Kalman filter based PLL (Phase Lock Loop), is performed in terms of mean square error of the phase estimate and mean time to first slip. Results show that the proposed method outperforms the conventional linear filter with respect to both metrics, especially at low signal-to-noise ratio.

show abstract

“…In what follows, performance of the proposed RVB estimator ( 20) is assessed numerically on synthetic data and compared to a KF-based PLL [18].…”

Section: Numerical Simulationsmentioning

confidence: 99%

Robust estimation of high-order phase dynamics using Variational Bayes inference

Fabozzi

Bidon

Roche

2021

ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

View full text Add to dashboard Cite

show abstract

“…The code discriminator variance

and frequency discriminator variance

can be approximated as follows [ 21 , 22 ]:

where

is the carrier-to-noise ratio in Hz.…”

Section: Conventional Mimu/gnss Utc Integration Architecturementioning

confidence: 99%

A New MIMU/GNSS Ultra-Tightly Coupled Integration Architecture for Mitigating Abrupt Changes of Frequency Tracking Errors

Liu

et al. 2020

Micromachines

View full text Add to dashboard Cite

We present a new ultra-tightly coupled (UTC) integration architecture of a micro-electromechanical inertial measurement unit (MIMU) and global navigation satellite system (GNSS) to reduce the performance degradation caused by abrupt changes of frequency tracking errors. A large frequency error will lead to a decrease in the carrier-to-noise ratio (C/N0) estimate and an increase in the code discriminator estimation error. The disruptive effects of frequency errors on the estimation of C/N0 and on the code discriminator are quantitatively evaluated via theoretical analyses and Monte Carlo simulations. The new MIMU/GNSS UTC architecture introduces a large frequency error detector and a refined frequency processor based on a retuned frequency in each tracking channel. In addition, an adaptive channel prefilter with multiple fading factors is introduced as an alternate to the conventional prefilter. Numerical simulations based on a highly dynamic trajectory are used to assess performance. The simulation results show that when there is an abrupt step change in the frequency tracking error, the new UTC architecture can effectively suppress the divergence of navigation solutions and the loss of tracking lock, and can significantly reduce the deviation of the C/N0 estimation.

show abstract

“…The main advantage of the Kalman filter tracking is that the loop filter bandwidth can be optimally adjusted through the change of Kalman gain as been discussed in [13], [14] and [15].…”

Section: B Kalman Filter Based Carrier Phase Trackingmentioning

confidence: 99%

“…3) With the ML Doppler and Doppler rate estimate available, the Doppler-compensated correlation sequence can now be written as P (2) [k] = P (1) [k]e −j2πf D,M L , , 1 ≤ k < K − 1. (15) and the maximum likelihood carrier phase estimate will beφ…”

Section: B Maximum Likelihood Carrier Phase Trackingmentioning

confidence: 99%

Performance comparison of Kalman filter and maximum likelihood carrier phase tracking for weak GNSS signals

Petovello

2015

2015 International Conference on Indoor Positioning and Indoor Navigation (IPIN)

View full text Add to dashboard Cite

GNSS carrier phase measurement capability is one of the most important features for high performance/accuracy receivers. However significant signal attenuation due to blockage and multipath as experienced indoors for example, degrades carrier phase quality in standard carrier phase tracking loops using PLL or KF-PLL. Under such conditions, the receiver may not be able to generate reliable carrier phase measurements either due to weak signal, fading or fragility of conventional tracking loops. One contribution of this paper is the proposed decoupled maximum likelihood carrier phase, Doppler and Doppler rate tracking architecture. This approach first independently estimates Doppler rate and Doppler based on power spectra and then estimates the carrier phase if possible. In order to assess the actual carrier phase measurement quality, controlled simulation is also conducted after analyzing the overall phase tracking performance. Double differenced carrier phase results as well as RTK solutions show that the proposed method works well and is able to generate reliable carrier phase measurement and centimeter level solution when the carrier-to-noise-density ratio (C/N0) is about 20 dB-Hz.

show abstract

Kalman filter-based architecture for robust and high-sensitivity tracking in GNSS receivers

Cited by 20 publications

References 6 publications

Robust estimation of high-order phase dynamics using Variational Bayes inference

Robust estimation of high-order phase dynamics using Variational Bayes inference

A New MIMU/GNSS Ultra-Tightly Coupled Integration Architecture for Mitigating Abrupt Changes of Frequency Tracking Errors

Performance comparison of Kalman filter and maximum likelihood carrier phase tracking for weak GNSS signals

Contact Info

Product

Resources

About