Abstract:

Feature-aided data association (FADA), as a novel and effective approach for improving track maintenance, has been a hot spot in the area of targets tracking under complicated environment such as dense clutter or multiple near spaced targets, and it has a good prospect of application. Based on the extensive investigation of published literatures, the foundational principle of FADA is represented at the beginning of this paper, followed by scientific categorization of the target features and association algorithms. The typical FADA application instances are surveyed in detail, and the direction of future progress is also discussed.