Abstract: The infrared sensor and ESM are important parts of military multisensor information fusion system. A track-to-track association (T2TA) algorithm using grey relational degree and classification information is presented to solve the problem of T2TA between the infrared sensor and ESM. In this algorithm, track sequences from the infrared sensor and ESM are considered as functions of discrete time and the grey relational matrix is formed by calculating the B-mode grey relational degree between tracks. Second, the validity of classification information is evaluated through the unitary entropy. According to the affiliation between targets and radiant sources, evidences in different frames are transformed into the same frame by the theory of valuation-based system (VBS). Then the consistency of different evidences is weighed by Jousselme distance and the association matrix for classification information is formed. Finally, track-to-track association is performed by using the grey relational matrix and the association matrix for classification information jointly. The simulation results show that the T2TA algorithm based on grey relational degree has a higher rate of correct association when the usable data are sufficient, and the T2TA algorithm based on classification-aided grey relational degree has a better association performance if the classification effects of the sensors are well.