Satellite Positioning Technology Based on Particle Filter and Kalman Filter Algorithms
This graduate thesis project implements satellite positioning technology using Particle Filter (PF) and Kalman Filter (KF) methods. The attachment includes complete MATLAB implementations for wireless channel estimation and equalization, Time Difference of Arrival (TDOA) ranging, and Interacting Multiple Model-Kalman Filter (IMM-KF) algorithms. The code features practical implementations of Bayesian filtering techniques and statistical signal processing, providing valuable resources for developers working on wireless positioning systems. Exclusive contribution to the research community.