The interacting multiple model algorithm for accurate state estimation of maneuvering targets
Anthony F. Genovese · Johns Hopkins APL technical digest · 2001
Accurate state estimation of targets with changing dynamics can be achieved through the use of multiple filter models. The interacting multiple model (IMM) algorithm provides a structure to efficiently manage multiple filter models. Design of an IMM requires selection of the number and type of filter models and selection of each of the individual filter parameters. In this article the results for five filter models on 10 target trajectory segments are discussed and compared. The complexity of the filter models increases from a single constant velocity model to a three-model IMM filter. The results show that the overall performance of the state estimates, for most targets, improves as the complexity of the filter models increases. Selection of IMM filter parameters is addressed and results are provided to show that performance of the IMM appears to be relatively insensitive to large changes in filter parameters. The performance of an IMM is primarily determined by the selection of the component filter models.