基于主/被动雷达双传感器的自适应跟踪融合算法

Adaptive Track Fusion for Active/Passive Radar Sensor

在主、被动雷达双传感器目标跟踪背景下,提出一种自适应数据融合算法。跟踪同一个目标的主、被动雷达观测数据由线性卡尔曼滤波器来处理,与主/被动雷达对应的两个跟踪器的输出数据被发送到一个中央节点,在这个节点中,包含了两个由在线跟踪信息构成的指标变量,将这些指标与设定的阈值进行对比,即通过二者的逻辑判断结果来选择用于得到整体评估的方法,其中对阈值的选择决定了融合算法融合精度与计算量的平衡点。仿真结果表明,这种融合算法有很好的融合效果。

An adaptive fusion algorithm is presented based on active/passive radar sensor target tracking. The measurements of the two sensors tracking the same target are processed by linear kalman filters. The outputs of the local trackers are sent to the central node, which contains two index variables with on-line tracking information. The global estimate is obtained by comparison or logic judgments between these index variables and the thresholds. The values of the thresholds govern the trade-off between accuracy and computational burden. Simulation shows that the fusion algorithm has good fusion results.