A Data Association Approach for Plot-Sequences Outputted by Multi-Frame Track-Before-Detect

This paper addresses the data association problem with respect to the multi-frame track-before-detect (MF-TBD). Different from the classical target detection and tracking approaches which declare target and update tracks for each single frame, the MF-TBD can achieve superior performance by integrating target energy over several consecutive frames, especially for dim or fluctuating targets. Moreover, with jointly processing consecutive frames of raw data, the outputs of MF-TBD are plot-sequences. However, in the single-target or multi-target scenario, there needs to assign the plot-sequences to the existing trajectories. In other words, MF-TBD is not a complete target detection and tracking system, or rather, the further tracking treatments are needed, such as the association step. In this paper, by referring to the existing works of data association methods, a novel data association approach for the plot-sequences outputted by MF-TBD is developed. Last, the simulation results show that the proposed algorithm can correctly associate target trajectories with the corresponding plot-sequences and significantly enhance the tracking performance compared with the traditional tracking algorithm.