Infrared focal plane array attitude measurement method based on adaptive fault-tolerant extended Kalman filter

To improve the anti-jamming ability of infrared attitude measurement methods, the infrared focal plane array (IRFPA) fault diagnosis method was investigated with regard to small-region and full-region infrared interference, respectively. An adaptive fault-tolerant extended Kalman filter algorithm is proposed to actively remove the infrared interference data in the case of small-region infrared interference and carry out attitude estimation with the mathematical model under full-region infrared interference. The results reveal that the adaptive faulttolerant extended Kalman filter has stronger anti-jamming ability compared with the conventional extended Kalman filter. Additionally, the adaptive fault-tolerant extended Kalman filter can maintain the attitude estimation accuracy of ?0.8? when full-region infrared interference doesn?t exist or if most IRFPA data are reliable. Apart from missile navigation, the framework of the adaptive fault-tolerant extended Kalman filter can be applied to almost all applications using extended Kalman filter, such as aircraft, vehicular navigation, indoor positioning, and target tracking, etc.

Automated summary

The study investigated the fault diagnosis method of Infrared Focal Plane Array (IRFPA) and proposed an adaptive fault-tolerant extended Kalman filter algorithm to improve anti-jamming ability and maintain attitude estimation accuracy in different infrared interference scenarios.