This codebase contains many errors; none of the contributors were professionals in this field. I have left the code as is for those who eventually find their way here.

The code was converted from MATLAB, and there are numerous open‑source implementations available. For the original MATLAB version by Ángel García‑Fernández, see: https://github.com/Agarciafernandez/MTT

Random Finite Set (RFS) theory provides an elegant framework that incorporates set‑cardinality dynamics into the propagation process. It can be applied to many existing methods, which has led to a large number of publications.

The more interesting element of this set of code is when it is applied to the nuScence dataset. I would caution against taking any of the papers at its face value. This is a topic that the most valuable thing really, is the code, where all the details are recorded.

The Poisson multi‑Bernoulli mixture (PMBM) filter can be viewed as a kitchen sink approach, wrapping the theoretical framework on established multiple‑hypothesis stuff.