GNSS have established themselves as the dominant positioning technology to provide location and navigation solutions with high reliability and accuracy with low-cost portable user devices. However, receiver performance can be significantly affected by operational environments. High attenuation and severe multipath fading degrade the signal tracking performance and limit the use of GNSS in indoor and urban environments. Therefore, this thesis focuses on enhancements of a context-aware high sensitivity software GNSS receiver.
To improve the GNSS signal tracking sensitivity, three levels of effort have been made. Firstly, four signal integrators, namely bit aiding coherent integrator, bit extracting coherent integrator, magnitude non-coherent integrator and squaring non-coherent integrator are developed and tested in the high sensitivity GNSS software receiver GSNRx-hsTM to increase the processing gain. While bit aiding coherent integrator utilizes time-tagged external data bit aiding, others do not require external data bit aiding. Secondly, three multi-correlator based frequency estimators, namely the FFT-based maximum-likelihood frequency estimator, the fast-slow frequency discriminator and the power-based frequency discriminator, are developed to improve the weak carrier tracking. Simulations show that these frequency estimators can provide about 4 to 5 dB gain compared to the traditional phase-different discriminators. The third effort is the development of the centralized vector-based tracking loops, the decentralized vector-based tracking loop, and the navigation-domain tracking loop. Using a GPS only constellation, it is shown that vector tracking can provide 2 to 6 dB improvements over scalar tracking. From tests with hardware simulated data, even without data bit aiding, the developed centralized and decentralized vector-based tracking loops with the multi-correlator frequency discriminator and the navigation-domain tracking loops can track signals as low as 8 dB-Hz. Field test conducted in a typical North American house shown that the centralized vector-based tracking loop and the scalar-based tracking loop can successfully track signals in a basement and provide metre-level position.
As the high sensitivity tracking techniques developed herein are different from conventional tracking methods, metrics that can be used to indicate the environment change and allow the receiver to have context-awareness are proposed and explored. From experiments conducted in residential homes, it is found that the sole use of C/N0 values to detect the transition between outdoors and indoors is optimistic; in contrast, it is found that the Ricean K-factor, can detect outdoor-to-indoor transitions by capturing the C/N0 variation due to multipath fading and allow the receiver to adjust the processing strategy before the transition happen.