Analyzing AUV Systems Using Particle Filter in Matlab

This project focuses on the application of particle filters in the context of autonomous underwater vehicles (AUVs). It utilizes Matlab to simulate and analyze the performance of these filters, particularly in scenarios involving sensor fusion and the handling of noisy data. The project details the implementation of particle filters, including techniques for adding noise to maintain population diversity and methods for resampling. Comparisons are made with Kalman filters to evaluate the effectiveness and efficiency of particle filters in estimating the function of AUVs. The project also examines the use of acoustic technologies and the challenges associated with communication and localization in underwater environments. The Matlab code is used to generate plots and simulate the behavior of the filters. The project concludes with a discussion of the advantages of particle filters for AUVs and their potential for improving the efficiency of underwater systems.