DTC Project 10.2 − Phase II • Multi-Sensor Tracking and Classification (2007 − 2010)

This is a project sponsored by the Data & Information Fusion - Defence Technology Centre (DIF/DTC), UK. The objective of this phase is more challenging because the objects to be tracked may no longer be travelling independently but in a coordinated format. Examples of these objects are coordinated flights of aircrafts and convoys of ground vehicles.

To tackle this problem, sophisticated interaction models for individuals within a group will be formulated, based upon pairwise spatio-temporal interaction models. Ultimately the methods will be developed in order to perform automatic convoy spotting where these convoys may have different intentions that may evolve with time. The required computational methodology will focus on multi-target Bayesian models using combinations of particle filter and Markov chain Monte Carlo methods. A particular methodological focus will be the scalability of the methods with group size. It has been advised that data from a commercial high range-accuracy radar, where individual targets result in multiple resolved detections, will be provided to help guide the research.

Furthermore, in this project we also will study the characteristics of large groups, or ‘clouds?of objects, in which individuals cannot be reliably tracked, but the whole group can be tracked through conglomeration of the many returns made by individuals in the cloud over a potentially large spatial area. It is planned to extend the use of Poisson models for clouds to achieve this aim, which removes the necessity to consider data association explicitly, hence making the framework tractable.