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本文从理论上讨论杂波环境中,多传感器数据融合对目标航迹丢失的改善。通过建立融合预测估计误差的转移概率密度函数,分析了目标航迹丢失的机理。在“最近邻”关联准则下,计算了融合航迹维持和融合航迹起始时的跟踪性能——融合航迹平均丢失时间和融合航迹累积丢失概率与杂波密度的关系,并与单传感器的情形作了比较。结果表明,多传感器的航迹融合减小了目标丢失的可能性,提高了跟踪性能。这一结论对进一步理解数据融合的作用具有重要的理论意义。
This paper theoretically discusses the improvement of target track loss in multi-sensor data fusion in clutter environment. The mechanism of target track loss is analyzed by establishing a transition probability density function which fuses prediction error. Under the “nearest neighbor” association criterion, the tracking performance at the beginning of fusion trajectory maintenance and fusion trajectory is calculated - the relationship between the average loss time of fusion trajectory and the cumulative loss probability of fusion trajectory and the clutter density, The situation of the sensor is compared. The results show that the multi-sensor trajectory fusion reduces the possibility of target loss and improves the tracking performance. This conclusion has important theoretical significance for further understanding of the role of data fusion.