Measurement preprocessing approach for target tracking in a cluttered environment

The paper presents a novel measurement preprocessing technique to enhance the performance of conventional Kalman-filter-based tracking algorithms. Received measurements are preprocessed, based on a maximum-likelihood estimation approach. Simulation results show the superior performance of this approach both in clean and cluttered environments