THEORETICAL ANALYSIS OF IMPROVEMENT OF TRACK LOSS IN CLUTTER WITH MULTISENSOR DATA FUSION
杂波中多传感器数据融合改善目标航迹丢失的理论分析

The paper analyses the improvement of track loss in clutter with multisensor data fusion. By detemination of the transition probability desity function for the fusion prediction error, one can study the mechanism of track loss analytically. For nearest-neighbor association algorithm, the paper studies the fusion tracking performance parameters,such as mean time to lose fusion track and the fraction of lost fusion track versus the normalized clutter density, for track continuation and track initiation, respectively. A comparison of the results obtained with the case of a single sensor is presented. These results show that the fusion tracks of multisensor reduce the possibility of track loss and improve the tracking performance. The analysis is of great importance for further understanding the action of data fusion.