GNSS/5G Hybridization for urban navigation

Over the past few years, the need for positioning, and thus the number of positioning services in general, has been in constant growth. This need for positioning has been increasingly focused on constrained environments, such as urban or indoor environments, where GNSS is known to have significant limitations: multipath as well as the lack of Line-of-Sight satellite visibility degrades the GNSS positioning solution and makes it unsuitable for some urban or indoor applications. In order to improve the GNSS positioning performance in constrained environments, many solutions are already available: hybridization with additional sensors or the use of signals of opportunity for example. Concerning SoO, mobile communication signals, such as the 4G Long Term Evolution or 5G, are naturally envisioned for positioning. Indeed, a significant number of users are expected to be “connected-users” and 5G systems offers promising opportunities. 5G technology is being standardized at 3GPP; the first complete release of 5G specifications, Release-15, was provided to the community in June 2018. 5G is an emerging technology and its positioning performance, as well as a potential generic receiver scheme to conduct positioning operations, is still under analysis. In order to study the potential capabilities provided by 5G systems and to develop a 5Gbased generic positioning module scheme, the first fundamental step is to develop mathematical models of the processed 5G signals at each stage of the receiver for realistic propagation channel models: the mathematical expression of the useful received 5G signal as well as the AWG (Additive White Gaussian) noise statistics. In the Ph.D., the focus is given to the correlation operation which is the basic function implemented by typical ranging modules for 4G LTE signals, DVB signals, and GNSS. In fact, the knowledge of the correlation output mathematical model could allow for the development of optimal 5G signal processing techniques for ranging positioning. Previous efforts were made to provide mathematical models of received signals at the different receiver signal processing stages for signals with similar structures to 5G signals – Orthogonal ²Frequency Division Multiplexing (OFDM) signals as defined in 3GPP standard. OFDM signal-type correlator output mathematical model and acquisition techniques were derived. Moreover, tracking techniques were proposed, analyzed and tested based on the correlator output mathematical model. However, these models were derived by assuming a constant propagation channel over the duration of the correlation. Unfortunately, when the Channel Impulse Response (CIR) provided by a realistic propagation channel is not considered to be constant over the duration of the correlation, the correlator output mathematical models are slightly different from the mathematical models proposed in the literature