MATLAB Implementation of Particle Filter Algorithms: PF, EKPF, UKPF with Resampling Methods

In this comprehensive article, we provide detailed coverage of particle filter algorithms, including standard Particle Filter (PF), Extended Kalman Particle Filter (EKPF), and Unscented Kalman Particle Filter (UKPF), along with various resampling methodologies. We examine the strengths and limitations of each algorithm and offer extensive learning documentation accompanied by practical MATLAB implementations. The implementations include key functions for particle initialization, importance sampling, weight calculation, and different resampling strategies such as systematic resampling, multinomial resampling, and stratified resampling. We present real-world application scenarios demonstrating how these algorithms perform in practical settings. This resource enables readers to gain deep understanding of particle filtering techniques and provides valuable reference material for research and implementation projects, with code examples highlighting algorithm-specific formulations and computational considerations for optimal performance.