Set value‐based dynamic model development for non‐linear manoeuvring target tracking problem in the presence of unknown but bounded disturbances

Abstract

The stochastic models developed for the manoeuvring target tracking (MTT) problem do not exhibit good performance owing to the lack of sufficient information about uncertainties. Moreover, each of the MTT models can be used for limited target manoeuvres. An ‘unknown but bounded’ (UBB)-based non-linear dynamic model for modelling time-dependent acceleration and model uncertainties is proposed for addressing the aforementioned problems. In the UBB approach, uncertainties and target manoeuvre are modelled using information about their upper bounds only. The extended set membership filter can be used to estimate the target states and manoeuvre with this new dynamic model. In order to examine the stability of the proposed method, the input to state stability of the estimation error is analysed. Very good performance is achieved by the proposed dynamic model without precise information about the model uncertainties. The proposed MTT algorithm can be used to track both non-manoeuvring and manoeuvring targets. The theoretical development is verified using simulations and the results are compared with those of other MTT methods. These comparisons demonstrate that the performance of the proposed method is better.