Low-cost GPS/GLONASS Precise Positioning in Constrained Environment

GNSS and particularly GPS and GLONASS systems are currently used in some geodetic applications to obtain a centimeter-level precise position. Such a level of accuracy is obtained by performing complex processing on expensive high-end receivers and antennas, and by using precise corrections. Moreover, these applications are typically performed in clear-sky environments and cannot be applied in constrained environments. The constant improvement in GNSS availability and accuracy should allow the development of various applications in which precise positioning is required, such as automatic people transportation or advanced driver assistance systems. Moreover, the recent release on the market of low-cost receivers capable of delivering raw data from multiple constellations gives a glimpse of the potential improvement and the collapse in prices of precise positioning techniques. However, one of the challenge of road user precise positioning techniques is their availability in all types of environments potentially encountered, notably constrained environments (dense tree canopy, urban environments…). This difficulty is amplified by the use of low-cost receivers and antennas, which potentially deliver lower quality measurements. In this context the goal of this PhD study was to develop a precise positioning algorithm based on code, Doppler and carrier phase measurements from a low-cost receiver, potentially in a constrained environment. In particular, a precise positioning software based on RTK algorithm is described in this PhD study. It is demonstrated that GPS and GLONASS measurements from a low-cost receivers can be used to estimate carrier phase ambiguities as integers. The lower quality of measurements is handled by appropriately weighting and masking measurements, as well as performing an efficient outlier exclusion technique. Finally, an innovative cycle slip resolution technique is proposed. Two measurements campaigns were performed to assess the performance of the proposed algorithm. A horizontal position error 95th percentile of less than 70 centimeters is reached in a beltway environment in both campaigns, whereas a 95th percentile of less than 3.5 meters is reached in urban environment. Therefore, this study demonstrates the possibility of precisely estimating the position of a road user using low-cost hardware.