Advanced Tracking Loop Architectures for Multi-frequency GNSS Receiver
Bolla, Padma (2018)
Tampere University of Technology
2018
Teknis-taloudellinen tiedekunta - Faculty of Business and Technology Management
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Julkaisun pysyvä osoite on
https://urn.fi/URN:ISBN:978-952-15-4309-8
https://urn.fi/URN:ISBN:978-952-15-4309-8
Tiivistelmä
The multi-frequency Global Navigation Satellite System (GNSS) signals are designed to overcome the inherent performance limitations of single-frequency receivers. However, the processing of multiple frequency signals in a time-varying GNSS signal environment which are potentially affected by multipath, ionosphere scintillation, blockage, and interference is quite challenging, as each signal is influenced differently by channel effects according to its Radio Frequency (RF). In order to get benefit of synchronously/coherently generated multiple frequency signals, advanced receiver signal processing techniques need to be developed.
The aim of this research thesis is to extract the best performance benefits out of multifrequency GNSS signals in a time-varying GNSS signal environment. To accomplish this objective, it is necessary to analyze the multi-frequency signal characteristics and to investigate suitable signal processing algorithms in order to enable the best performance of each signal. The GNSS receiver position accuracy and reliability are majorly determined by the signal tracking-loop performance, hence, the primary focus of this thesis is on improving the tracking-loop performance of coherently generated multi-frequency signals.
In the first phase of this research, the performance of multi-frequency GNSS signals is analyzed using conventional signal processing algorithms. Furthermore, the performance of a combination of multi-frequency signals is evaluated in order to find the optimum two-frequency signal combination for standalone and differential positioning applications. The limitations of the conventional multi-frequency signal processing algorithms are identified and an optimum dual-frequency signal processing architecture is proposed for robust and precise positioning applications.
By making use of the inherent linear relation between the Line-of-Sight (LOS) Doppler shifts of multi-frequency GNSS signals, a computationally efficient Centralized Dynamics Tracking Loop (CTL) architecture is also proposed. In the CTL architecture, the common geometric Doppler shift in the received multi-frequency signals is estimated using a higher-order wide-band filter by making use of multiple frequency channel measurements in a coordinated manner. Additionally, the residual-phase variations specific to each frequency channel are tracked using Phase Lock Loop (PLL) with a narrow bandwidth filter. The CTL filter provides the geometric Doppler shift aid to individual frequency channels. The common Doppler-aided narrow-band signal tracking enhances the signal tracking sensitivity and robustness to the in-band interference in each frequency channel. This further reduces the noise in the linear combination of pseudorange observations.
In real GNSS signal environment, multiple frequency signals are often subjected to intentional or unintentional RF interference either at the same time or at different time instants. Moreover, each of these signals is influenced differently by RF interference. To track signals in such time-varying signal conditions, the CTL using an Adaptive Kalman Filter (AKF) is proposed to enable an adaptive tracking loop bandwidth in response to received signal power level and signal dynamics. The central task of the AKF is to effectively blend multiple frequency carrier-phase observations to estimate the common geometric Doppler frequency of received multiple frequency signals. A suitable collaboration in multi-frequency channel tracking using centralized dynamics tracking loop enables a robust carrier tracking even if some of the frequency channels are affected by ionospheric scintillation, multipath, or interference.
The performance of the proposed multi-frequency GNSS signal processing algorithms is demonstrated using analytical methods and experimental results based on live satellite data collected over GPS L1, L2C, and L5 signal frequencies. The dual-frequency signal processing architecture proposed in this research thesis has reduced the position error by 50%. The centralized dynamics multi-frequency carrier tracking loop has enhanced the individual channel tracking loop threshold by 7 dB in challenging signal conditions.
The aim of this research thesis is to extract the best performance benefits out of multifrequency GNSS signals in a time-varying GNSS signal environment. To accomplish this objective, it is necessary to analyze the multi-frequency signal characteristics and to investigate suitable signal processing algorithms in order to enable the best performance of each signal. The GNSS receiver position accuracy and reliability are majorly determined by the signal tracking-loop performance, hence, the primary focus of this thesis is on improving the tracking-loop performance of coherently generated multi-frequency signals.
In the first phase of this research, the performance of multi-frequency GNSS signals is analyzed using conventional signal processing algorithms. Furthermore, the performance of a combination of multi-frequency signals is evaluated in order to find the optimum two-frequency signal combination for standalone and differential positioning applications. The limitations of the conventional multi-frequency signal processing algorithms are identified and an optimum dual-frequency signal processing architecture is proposed for robust and precise positioning applications.
By making use of the inherent linear relation between the Line-of-Sight (LOS) Doppler shifts of multi-frequency GNSS signals, a computationally efficient Centralized Dynamics Tracking Loop (CTL) architecture is also proposed. In the CTL architecture, the common geometric Doppler shift in the received multi-frequency signals is estimated using a higher-order wide-band filter by making use of multiple frequency channel measurements in a coordinated manner. Additionally, the residual-phase variations specific to each frequency channel are tracked using Phase Lock Loop (PLL) with a narrow bandwidth filter. The CTL filter provides the geometric Doppler shift aid to individual frequency channels. The common Doppler-aided narrow-band signal tracking enhances the signal tracking sensitivity and robustness to the in-band interference in each frequency channel. This further reduces the noise in the linear combination of pseudorange observations.
In real GNSS signal environment, multiple frequency signals are often subjected to intentional or unintentional RF interference either at the same time or at different time instants. Moreover, each of these signals is influenced differently by RF interference. To track signals in such time-varying signal conditions, the CTL using an Adaptive Kalman Filter (AKF) is proposed to enable an adaptive tracking loop bandwidth in response to received signal power level and signal dynamics. The central task of the AKF is to effectively blend multiple frequency carrier-phase observations to estimate the common geometric Doppler frequency of received multiple frequency signals. A suitable collaboration in multi-frequency channel tracking using centralized dynamics tracking loop enables a robust carrier tracking even if some of the frequency channels are affected by ionospheric scintillation, multipath, or interference.
The performance of the proposed multi-frequency GNSS signal processing algorithms is demonstrated using analytical methods and experimental results based on live satellite data collected over GPS L1, L2C, and L5 signal frequencies. The dual-frequency signal processing architecture proposed in this research thesis has reduced the position error by 50%. The centralized dynamics multi-frequency carrier tracking loop has enhanced the individual channel tracking loop threshold by 7 dB in challenging signal conditions.
Kokoelmat
- Väitöskirjat [4864]