Probability Hypothesis Density Filter Implementation and Application

In this project, we explore multipletarget tracking and filtering in noisecluttered sensing environments. Specifically, we formulate the Gaussian Mixture Probability Hypothesis Density (GM-PHD) filter, the analytical solution to multi-target Bayes filtering under linear Gaussian assumptions and time-varying numbers of targets. We implement the GM-PHD filter as a Julia package, showcase simulations of its effective use, and benchmark against examples in literature.