Maneuvering target tracking based on combined stochastic differential equations and garch process

In this paper, we propose a new model to track a maneuvering target with abrupt accelerations. We utilize the stochastic differential equation (SDE) to model acceleration of a maneuvering target with GARCH process as the model for the SDE volatility. The proposed tracking algorithm operates in both the non-manoeuvring and the manoeuvring modes and the manoeuvre detection procedure is eliminated. In the proposed scheme, the original state and stochastic volatility are estimated simultaneously with a particle filter. We show analytically that target tracking performance by considering GARCH acceleration model is improved. Finally, the effectiveness and capabilities of our proposed strategy are demonstrated and validated through a simulation study.