Branko Ristic

TL;DR: Part I Theoretical concepts: introduction suboptimal nonlinear filters a tutorial on particle filters Cramer-Rao bounds for nonlinear filtering and tracking applications: tracking a ballistic object bearings-only tracking range- only tracking bistatic radar tracking targets through blind Doppler terrain aided tracking detection and tracking of stealthy targets group and extended object tracking.

TL;DR: In this article, the problem of tracking a ballistic object in the reentry phase by processing radar measurements is studied and a suitable (highly nonlinear) model of target motion is developed and the theoretical Cramer-Rao lower bounds of estimation error are derived.

TL;DR: A mathematically rigorous metric is proposed for performance evaluation of multi-target tracking algorithms that is defined on the space of finite sets of tracks and incorporates the labeling error.

TL;DR: This work investigates the problem of bearings-only tracking of manoeuvring targets using particle filters (PFs) and confirms the superiority of the PFs for this difficult nonlinear tracking problem.

TL;DR: A new extension of the PHD and CPHD filters, which distinguishes between the persistent and the newborn targets is presented, which enables us to adaptively design the target birth intensity at each scan using the received measurements.