Target data association in communication constrained environment using CART: Compressed adaptive reference topology

Target data association is one of the key procedures of multi-sensor data fusion and many algorithms have been developed to solve the traditional association problem. However, performance of traditional methods is degraded in communication constrained environment. In this paper, an approach is proposed to solve the problem of target data association in communication constrained environment. In the algorithm, we extract, quantify and compress the reference topology feature in order to complete the association with lower amount of data than traditional methods. Simulation results show that the proposed algorithm can achieve higher correct rate in target data association than traditional methods with the same data volume.