Measurement preprocessing-based estimation approach to target tracking

In this paper, we present a measurement preprocessing-based state estimation algorithm for maneuvering target tracking. The preprocessing scheme on received measurements is employed to reduce the covariance of measurement errors. This can be achieved by using a maximum likelihood method for yielding target´s estimated accelerations and velocities which result in preprocessed measurements. Preprocessed measurements are then utilized as inputs to a state estimator for improving the estimation performance. We then integrate the proposed method into the variable dimension filter (VDF) as the measurement-preprocessing based VDF without altering the functional structure of the VDF. Simulation results show that the proposed measurement-preprocessing based VDF can achieve superior performance.