New methods and architectures for high sensitivity hybrid GNSS receivers in challenging environments

GNSS satellite navigation systems are constantly evolving and have been already used in many applications. With the advent of the new systems Galileo and BeiDou as well as the modernization of GPS and GLONASS systems, new satellites and numerous new frequencies and signals will appear in the coming years and will open door to countless new applications that are currently impossible. The rapid evolution of mobile telephony and personal navigation devices (PND) requires better use of navigation systems in non-ideal environments, especially the need for positioning in deep urban area. On the one hand, users are waiting for a high positioning accuracy, because of the proximity to various points of interest. On the other hand, urban environment brings specific difficulties in receiving GNSS signals. GNSS navigation signals cannot be properly captured in urban and "indoor" environments. Signal levels are very low and it is almost impossible to acquire and track signals autonomously because of the strong attenuation of signals due to obstacles. In addition, indoor and urban positioning are also subject to multipath problems, masking, interference and jamming. Under these conditions, we must be able to process highly degraded or very short signals that do not allow the receiver to go through the tracking process. Thus, this leads us to the need to rethink the architecture of GNSS receiver for modern applications. This thesis project consists of developing new GNSS methods and architectures of high sensitivity and robustness to signal degradations and designing new algorithms integrated into a hybrid GNSS receiver capable of operating in deep urban environments. The methodology involves the use of the new concept of “Collective Detection (CD)”, also called “collaborative acquisition”. The collaborative approach that treats multi-satellite signals all together opens an interesting solution. Many techniques exist in the literature to solve the problems of positioning in urban environments, but we propose the new Collective Detection approach because of its performance as both a Direct Positioning (DP) method, providing a coarse position/clock-bias solution directly from acquisition, and High-Sensitivity (HS) acquisition method, by application of vector detection of all satellites in view. Indeed, the correct combination of the correlation values of several satellites can reduce the required Carrier-to-Noise Ratio (C/No) level of the satellite signals which cannot be acquired individually by standard signal processing (acquisition and tracking) but make it possible to use them constructively to a positioning solution. The combination of different GNSS signals can considerably increase the acquisition sensitivity of the receiver. Despite the advantages of this approach, it also has drawbacks such as the high computational burden because of the large number of candidate points in the position/clock-bias domain. Thus, the work proposed in this thesis consists of reducing the complexity of the CD by optimizing the search for candidate points in position/clock-bias domain. Finally, the goal is to apply the CD approach to Cooperative GNSS Positioning for modern navigation in harsh environments. For that, algorithms for optimally exploiting receiver resources by selecting the best satellites or the reference station will be developed according to certain criteria such as the C/No level, the elevation angle, and the geometric configuration of the visible satellites. The ultimate goal is to propose a design of a new smart receiver “High Sensitivity Cognitive GNSS Receiver (HSCGR)” to optimally receive and process GNSS signals