基于多机载预警雷达的机动目标融合跟踪方法  

Research on Maneuvering Targets Fusion Tracking Method Based on Multi-airborne Early Warning Radars Fusion

作　　者：戴瑜 龙文佳[1] DAI Yu;LONG Wen-jia(Zhixing College of Hubei University,Wuhan 430019,China)

机构地区：[1]湖北大学知行学院,武汉430019

出　　处：《火力与指挥控制》2021年第4期136-140,共5页Fire Control & Command Control

摘　　要：机动目标跟踪是多机载预警雷达数据融合中的一个难点,传统的卡尔曼滤波本身不足以解决该问题。基于量测噪声协方差估计设计了一种可适用于机动目标的卡尔曼滤波器;引入了协方差交集,提出了一种针对多机载预警雷达数据融合中机动目标跟踪的新方法。仿真实验表明,该方法能够成功稳定地跟踪机动目标,与现有的主流方法相比,该方法的误差性能是最佳的。Tracking of maneuvering targets is a difficult problem in data fusion of multi-airborne early warning radars,and the traditional Kalman filter itself cannot solve this problem sufficiently.Firstly,Kalman filter for maneuvering targets is designed based on the measurement noise covariance estimation.Then a covariance intersection is introduced,and a new method for maneuvering targets tracking in multi airborne early warning radar data fusion is proposed.The simulation experiments show that the proposed method can track the maneuvering targets successfully and steadily.Compared with the existing mainstream methods,the error performance of the proposed method is optimal.

关 键 词：机动目标 跟踪 数据融合 卡尔曼滤波 滑动平均滤波器 

分 类 号：TN959[电子电信—信号与信息处理]