Abstract: Modified probabilitic data association filter （MPDAF） is now a more efficient approach to tracking multiple maneuvering targets in dense multi-return environment. But, when the density of returns increases, such approach will lose targets easily. To overcome this shortcoming, this paper puts forword an approach of risidual filter （RF） on the basis of MPDAF and reveals its inherent mechanism between RF and data association from two aspects of theoretical analysis and Monte Carlo simulation. The results show that the approach improves the catching ability of the tracker, the ability of rejecting extraneous returns in correlation regions, and the tracking performance greatly. The new approach is an efficient method for tracking multiple maneuvering targets in higher dense multi-return environment.