天线罩干扰下的雷达/红外复合导引头数据融合

针对雷达/红外复合导引头中存在天线罩折射以及外部干扰问题,在三维模型下,提出一种基于扩展卡尔曼滤波(EKF,Extended Kalman Filter)的多模型算法,对天线罩斜率进行估计,并将估计结果代入EKF,降低观测视线角中的天线罩折射干扰,形成最优局部估计.采用基于环境信息的加权因子法对雷达/红外局部估计结果进行融合,通过环境信息度量传感器测量结果的可信度,忽略不可信的局部估计结果.设计4组算例检验融合算法性能,仿真结果表明:所提算法可以准确估计天线罩斜率,合理并有效使用雷达/红外传感器信息,提高系统估计精度.

High accuracy data fusion of radar/infrared multi-mode guidance seeker with radar radome interference

In order to improve anti-interference ability of radar/infrared multi-pattern composite guidance seeker with radome refraction, a new multiple model radome slopes estimate algorithm based on extended Kalman filter(EKF) was proposed in the three dimensional engagement scenarios. The slopes estimates were utilized in EKF to degrade the radome refraction in measuring line-of-sight and to get the local optimal estimates. Both of partial estimation results were integrated with sensor weighted coefficients depended on the sensor contextual information, which was introduced to characterize the reliability of sensor. The invalidity signals would be rejected. The performance of the proposed fusion algorithm was examined by four examples. Simulation results show that the algorithm can appropriately use radar/infrared measurement with radome slopes effectively estimating to enhance the estimating accuracy.