一种主/被动雷达模糊数据融合算法

A Data Fusion Algorithm Active/Passive Radars Based on Fuzzy Logic

提出一种基于模糊逻辑的主/被动雷达传感器数据融合算法。首先将单个雷达的测量值通过时间校准后,将它们作为卡尔曼滤波器的输入分别滤波,然后再对滤波后的目标状态估计进行融合。融合算法基于卡尔曼滤波的协方差匹配关系,采用模糊推理得到数据融合的权值。最后将各传感器的卡尔曼滤波状态估计进行加权融合得到所需要的目标状态信息。采用该融合算法可以有效提高目标跟踪系统的抗干扰能力。仿真结果表明该算法有效。

A data fusion algorithm for active/passive radars based on fuzzy logic is proposed.The measurement vector of each radar is time calibrated,and then the calibrated measurement is estimated by Kalman filter.Finally,the estimated data of the target state is fused.The fusion algorithm is based on the matching relationship of estimated state covariance,and the fusion weights can be deduced by fuzzy inference.The proposed algorithm can significantly improve the resistance of the target tracking system to disturbances.Simulation results show that the proposed algorithm is effective.