Improvement in the Tracking Performance of a Maneuvering Target in the Presence of Clutter

The proposed work uses fixed lag smoothing on the interactive multiple model-integrated probabilistic data association algorithm (IMM-IPDA) to enhance its performance. This approach makes use of the advantages of the fixed lag smoothing algorithm to track the motion of a maneuvering target while it is surrounded by clutter. The suggested method provides a new mathematical foundation in terms of smoothing for mode probabilities in addition to the target trajectory state and target existence state by including the smoothing advantages. The suggested fixed lag smoothing IMM-IPDA (FLs IMM-IPDA) method's root mean square error (RMSE), true track rate (TTR), and mode probabilities are compared to those of other recent algorithms in the literature in this study. The results clearly show that the proposed algorithm outperformed the already-known methods in the literature in terms of these above parameters of interest.

Automated summary

The proposed fixed lag smoothing IMM-IPDA method utilizes the advantages of fixed lag smoothing algorithm to track maneuvering target in cluttered environment, showing superior performance compared to other recent algorithms in terms of mode probabilities, target trajectory state and target existence state.