An amplitude-aided multi-target tracking (MTT) exploits amplitude as well as spatial features for MTT. Compared to MTT using a spatial feature only, it can maintain its performance even in densely cluttered environment because more accurate association is achieved by using both features for likelihood evaluation between tracks and measurements. Therefore, the goal of this study is to review the state-of-the-art amplitude-aided MTT methods and compare each other extensively. For a fair comparison, a unified MTT framework is developed, and various methods are implemented and compared based on the same framework. On the challenging visual MTT datasets, the implemented methods are evaluated for several aspects such as accuracy, speed, sensitivity, and stability. Moreover, this study presents a summary of the extensive evaluation and guideline to select an appropriate method for amplitude-aided tracking.