--The data association problem arises whenever two or more sources collect data on a set of common objects without an obvious way to determine which object in one sensor’s labeling scheme corresponds to which object in another’s. This problem has a rich history within the tracking community, but there are a number of active research issues both for traditional kinematic tracking problems, and in emerging, non-kinematic domains. Papers are sought which advance the state of the art by addressing methods for: processing novel data types (e.g., image, network, or categorical data); accounting for bias or other forms of systematic cross-correlation between (possibly heterogeneous) sensors; associating data between three or more sensors; computing justifiable confidence estimates for association; using time-histories to avoid instantaneous association ambiguities (such as track-crossing issues); genealogical methods for maintaining accurate, rapidly searchable association histories; and handling data fused on the basis of computed associations while accounting for induced track correlation and/or potential errors in the association used. Other methods and issues that are not explicitly mentioned in this list but contribute to insight and understanding of the data association problem are also invited.

--Dr. Ferry has been active in the field of track-to-track association since joining Metron in 2004. He has developed the cohesive mathematical framework XMAP for data association, initially in collaboration with Lawrence Stone, which generalizes kinematic-only association to include output from feature extraction and object-type classification routines, publishing several papers on the topic and developing an algorithm (feature-ETOM) which has transitioned into an operational Missile Defense system (GMD). He has also collaborated with Roy Streit on similar work for NRL regarding the information-theoretic value of object-type identification data in multiple hypothesis correlation, and is currently the Principal Investigator of a project to developed feature-aided association for PEO IWS. Dr. Ferry is active in the area of network science as well, having been the Principal Investigator of three projects in this area, while publishing several papers and transitioning the technology developed to ONI. Before joining Metron, Dr. Ferry was a Research Scientist at the Center for Simulation of Advanced Rockets at the University of Illinois. There he published 19 papers on multiphase flow and computational methods for solid rocket motors. Dr. Ferry holds a Ph.D. in Applied Mathematics from Brown University, where his doctoral work applied group representation theory to the analysis of the global energetics of thermal convection, and an S.B. in Mathematics from the Massachusetts Institute of Technology.