Unified maneuvering model for target tracking by using range-rate measurement

A novel Unified maneuvering model (UMM) for tracking the target performed the complex curvilinear motion in two dimensions is presented, where the model is constructed by time-varying parameters and driven by the along-track and cross-track acceleration input, and the range rate plays a key role to update variable parameters online. In Cartesian coordinates, by incorporating the cross-track acceleration component which is estimated online by using the range-rate, and the alongtrack acceleration component which is determined under the assumption of zero-mean first order Markovian process, the proposed UMM exhibits highly self-adjustment capability to compensate the mismatch between the actual motion and the mathematic model adaptively, especially, shows a well capability to approximate the standard Interacting multiple model (IMM) under the situation of complex curvilinear motion and a higher level of the measurement noise. Simulation results validate our theory and show that UMM-based filtering is superior to that using the Current statistic model (CSM), and has a well approximation to IMM, meanwhile, has a low computational load substantially.