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.