Intended Audience: People wishing to understand the basic theory, results, and methods of multiple-target tracking from a standard Bayesian point of view without unnecetutoialary extensions, generalizations, or mathematical formalisms. Researchers desiring to learn how likelihood functions incorporate disparate types of information into data fusion solutions in a principled fashion.

Description: This tutorial is based on the book, Bayesian Multiple Target Tracking 2nd Ed. Its purpose is to present the basic results in multiple-target tracking from a Bayesian point of view. People who register will receive a complimentary copy of the book when they attend the tutorial.

Prerequisites: General familiarity with probabilistic concepts such as random variables, probability distributions, density functions, conditional probabilities, and expectations. Some familiarity with multivariate calculus and basic vector and matrix operations is also desirable.

Presenter: Lawrence D. Stone and Roy L. Streit