The Key to GNSS Ambiguity Resolution

One of the major obstacles in resolving ambiguities for longer baselines is the presence of unmodeled ionospheric delays. One technique to deal with this problem is to include ionospheric delay parameters in the observation equations, and estimate them as unknown states. The purpose of this article is to analyze this technique in light of the future signals that will be available through GPS modernization and the deployment of Galileo. A GNSS software simulator has been used to generate future signals from both GPS and Galileo. These simulated measurements have then been processed by newly developed GNSS processing software to give experimental results showing the effectiveness of ionospheric estimation and how this affects the reliability of ambiguity resolution. Among other functions, the simulator generates pseudorange and carrier phase measurements from GPS and Galileo satellites. The simulated measurements are corrupted by realistic levels of errors due to the troposphere, the ionosphere, multipath, and thermal noise. Software developed at the University of Calgary in Alberta, Canada, processes these simulated measurements using a Kalman filter. First, a float ambiguity solution is computed, and if desired, the Least Squares Ambiguity Decorrelation Adjustment (LAMBDA) technique is employed to search for integer ambiguities.