Robust Estimation Techniques for GNSS Positioning

Tracking and navigation problems are often solved using estimation methods that are based on least-squares and Kalman filtering techniques. It is well known that these classic methods are sensitive to unexpectedly large measurement errors. In this article we discuss some robust static and dynamic estimation methods that are designed to be insensitive against outlying observations. Positioning simulations and results of a field test where robust techniques are applied to pedestrian positioning using GPS pseudorange measurements are presented. The results indicate that robust techniques have potential in GNSS positioning.