Model Reduction

This lecture covers the process of model reduction in the context of satellite positioning systems, focusing on simplifications and normal equations for short baselines. It discusses the principles of form normals, simplifications, and the elimination of parameters to reduce the model complexity. The instructor explains the steps involved in the reduction process and provides examples of applying the techniques to real-world data. Additionally, the lecture introduces the Generalized Method of Wavelet Moments (GMWM) for stochastic calibration of sensors, showcasing its application in modeling and improving the accuracy of empirical wavelets.