Global navigation satellite system (GNSS) receivers use tracking loops to lock onto GNSS signals. Fixed loop settings limit the tracking performance against noise, receiver dynamics, and the current scenario. Adaptive tracking loops adjust these settings to achieve optimal performance for a given scenario. This paper evaluates the performance and complexity of state-of-the-art adaptive scalar tracking techniques used in modern digital GNSS receivers. Ideally, a tracking channel should be adjusted to both noisy and dynamic environments for optimal performance, defined by tracking precision and loop robustness. The difference between the average tracking jitter of the discriminator’s output and the square-root Cramér-Rao bound (CRB) indicates the loops’ tracking capability. The ability to maintain lock characterizes the robustness in highly dynamic scenarios. From a system perspective, the average lock indicator is chosen as a metric to measure the performance in terms of precision, whereas the average number of visible satellites being tracked indicates the system’s robustness against dynamics. The average of these metrics’ product at different noise levels leads to a reliable system performance metric. Adaptive tracking techniques, such as the fast adaptive bandwidth (FAB), the fuzzy logic (FL), and the loop-bandwidth control algorithm (LBCA), facilitate a trade-off for optimal performance. These adaptive tracking techniques are implemented in an open software interface GNSS hardware receiver. All three methods steer a third-order adaptive phase locked loop (PLL) and are tested in simulated scenarios emulating static and high-dynamic vehicular conditions. The measured tracking performance, system performance, and time complexity of each algorithm present a detailed analysis of the adaptive techniques. The results show that the LBCA with a piece-wise linear approximation is above the other adaptive loop-bandwidth tracking techniques while preserving the best performance and lowest time complexity. This technique achieves superior static and dynamic system performance being 1.5 times more complex than the traditional tracking loop.

This paper presents a loop-bandwidth control algorithm for adaptive scalar tracking loops used in modern digital global navigation satellite system (GNSS) receivers. This algorithm modifies the noise bandwidth of the loop filter. The updated loop-bandwidth balances the signal dynamics and noise through a weighting function. The agility of the estimators defines the sensitivity of the algorithm against dynamics. This algorithm is applicable to the delay-, frequency- or phase-locked-loop (DLL, FLL, PLL) and to any order loop-filter, making it simpler to incorporate than other methods. The algorithm is first analyzed and evaluated in a software receiver. Second, it is implemented in an open software interface GNSS hardware receiver for testing in simulated scenarios with real-world conditions. The scenarios represent different dynamics and noise cases. The results show the algorithm's generic usability and advantage over fixed loop settings, while preserving minimum tracking jitter and stability.

This paper evaluates the performance of robust adaptive tracking techniques with the direct-state Kalman filter (DSKF) used in modern digital global navigation satellite system (GNSS) receivers. Under the assumption of a well-known Gaussian distributed model of the states and the measurements, the DSKF adapts its coefficients optimally to achieve the minimum mean square error (MMSE). In time-varying scenarios, the measurements’ distribution changes over time due to noise, signal dynamics, multipath, and non-line-of-sight effects. These kinds of scenarios make difficult the search for a suitable measurement and process noise model, leading to a sub-optimal solution of the DSKF. The loop-bandwidth control algorithm (LBCA) can adapt the DSKF according to the time-varying scenario and improve its performance significantly. This study introduces two methods to adapt the DSKF using the LBCA: The LBCA-based DSKF and the LBCA-based lookup table (LUT)-DSKF. The former method adapts the steady-state process noise variance based on the LBCA’s loop bandwidth update. In contrast, the latter directly relates the loop bandwidth with the steady-state Kalman gains. The presented techniques are compared with the well-known state-of-the-art carrier-to-noise density ratio ($C/N_0$)-based DSKF. These adaptive tracking techniques are implemented in an open software interface GNSS hardware receiver. For each implementation, the receiver’s tracking performance and the system performance are evaluated in simulated scenarios with different dynamics and noise cases. Results confirm that the LBCA can be successfully applied to adapt the DSKF. The LBCA-based LUT-DSKF exhibits superior static and dynamic system performance compared to other adaptive tracking techniques using the DSKF while achieving the lowest complexity.

Interference events in the global navigation satellite system (GNSS) spectrum are becoming commonplace. Therefore, the likelihood of receiving multiple simultaneous interference signals is increasing. A common approach to such complex scenarios is to cascade multiple mitigation processors. This paper analyses the response of cascaded adaptive notch filtering (ANF) against two simultaneous frequency-modulated continuous-wave (FMCW) interferences. Results show that if the amplitude differences between the FMCW interferences are sufficient, then a cascaded approach can be successful. However, if the amplitudes are similar, then an ANF would lock onto the wrong frequency-typically a frequency between the two interferences-causing significant performance losses. This effect emphasizes the need for more advanced interference mitigation methods to overcome these limitations, such as the use of multi-spectral methods.

This paper analyzes the performance and complexity of state-of-the-art adaptive scalar tracking techniques used in modern digital global navigation satellite system (GNSS) receivers. Ideally, a tracking channel should be able to adjust to both noisy and dynamic environments for optimal performance. Precision and robustness define the performance of the tracking. The difference between the square root of the Cramer-Rao bound (CRB) and the average tracking jitter at the discriminator's output determines the precision of the tracking, whereas the speed of the response specifies the robustness of the tracking in high dynamic scenarios. The amount of operations required to implement a robust tracking technique indicates the complexity of the algorithm. The fast adaptive bandwidth, the fuzzy logic, and the loop-bandwidth control algorithm adaptive tracking techniques are first analyzed and evaluated in a software receiver. Second, these techniques are implemented in an open software interface GNSS hardware receiver for testing in simulated scenarios with real-world conditions. The scenarios represent different dynamics and noise cases. The results show the loop-bandwidth control algorithm's advantage over adaptive loop-bandwidth techniques while preserving good tracking performance and low complexity.

This paper evaluates the implementation of a low-complexity adaptive full direct-state Kalman filter (DSKF) for robust tracking of global navigation satellite system (GNSS) signals. The full DSKF includes frequency locked loop (FLL), delay locked loop (DLL), and phase locked loop (PLL) tracking schemes. The DSKF implementation in real-time applications requires a high computational cost. Additionally, the DSKF performance decays in time-varying scenarios where the statistical distribution of the measurements changes due to noise, signal dynamics, multi-path, and non-line-of-sight effects. This study derives the full lookup table (LUT)-DSKF: a simplified full DSKF considering the steady-state convergence of the Kalman gain. Moreover, an extended version of the loop-bandwidth control algorithm (LBCA) is presented to adapt the response time of the full LUT-DSKF. This adaptive tracking technique aims to increase the synchronization robustness in time-varying scenarios. The proposed tracking architecture is implemented in an GNSS hardware receiver with an open software interface. Different configurations of the adaptive full LUT-DSKF are evaluated in simulated scenarios with different dynamics and noise cases for each implementation. The results confirm that the LBCA used in the FLL-assisted-PLL (FAP) is essential to maintain a position, velocity, and time (PVT) fix in high dynamics.