Abstract
Gaussian mixture probability hypothesis density filter algorithm (GMPHDA), which is effective method for tracking unknown number of multi-target in strong clutter environment, has solid theoretical basis. But it is hard to track target by GMPHDA when the targets maneuver. To model maneuvering target, we introduce interacting multi-model (IMM) in GMPHDA by modeling maneuvering model of survival target and fusing probability hypothesis density of each model filter based on latest model probability, getting IMM-GMPHDA. The simulation results show that we can real-time track strong maneuvering and supersonic multi-target with IMM-GMPHDA, whose tracking precision can reach 70 m in multi-radar networking system, which meets the project requirement.
The National Nature Science Fund Project 61273001, Anhui Province Nature Science Fund Project 11040606M130.
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Ding, HL., Zhao, WB., Zhang, LZ. (2016). Study on Tracking Strong Maneuvering Targets Based on IMM-GMPHDA. In: Huang, DS., Jo, KH. (eds) Intelligent Computing Theories and Application. ICIC 2016. Lecture Notes in Computer Science(), vol 9772. Springer, Cham. https://doi.org/10.1007/978-3-319-42294-7_74
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DOI: https://doi.org/10.1007/978-3-319-42294-7_74
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