The Sequential Likelihood Ratio Test VSMM Algorithm for Maneuvering Target Tracking

摘要

The interacting multiple model state estimation approach is widely utilized for maneuvering target tracking. The IMM algorithm has a fixed model set structure which leads a dilemma that more models improve the accuracy but the use of too many models is as bad as that of too few models, and increases the computing burden. This paper presents a variable structure multiple model algorithm based on the sequential likelihood ratio test (SLAT-VSMM) that leads to a systematic treatment of model-set adaption. The new approach can increase the accuracy as well as decrease the computing burden by using the most likely model set at each time. The simulation of tracking an anti-ship missile shows the improvement of the system performance when we use the SLRT-VSMM approach.