Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1996 · 21 citations · 0 references
EngineeringMarine EngineeringOcean EngineeringMachine LearningSensor FusionUnderwater AcousticsData AssociationKalman FilteringManeuveringAccuracy-computational Cost TradeoffData Association In Sonar TrackingInteracting Multiple Model FilteringMarine Data FusionProbabilistic Data AssociationTarget TrackingUnderwater Target Tracking
This paper proposes a new fuzzy logic approach for solving the data association problem typically encountered in the application of target tracking. A single massive target maneuvering in a heavily-cluttered underwater environment is considered. The proposed fuzzy data association (FDA) approach is combined with an interacting multiple model (IMM) filter. The resultant IMM-FDA tracking algorithm is applied to estimate the state of the maneuvering target, and its performance is compared to that of a combination of an IMM filter and the probabilistic data association (PDA) scheme. The obtained results indicate that the IMM-FDA significantly outperforms the IMM-PDA at the expense of requiring more computational cost and introducing a short processing lag.