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 fault-tolerant 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 $\pm 0.8°$ 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.

为了提高红外姿态测量方法的抗干扰能力，分别针对小区域和全区域红外干扰，研究了红外焦平面阵列（IRFPA）故障诊断方法。提出了一种自适应容错扩展卡尔曼滤波算法，在小区域红外干扰情况下主动去除红外干扰数据，并在全区域红外干扰下利用数学模型进行姿态估计。结果表明，与传统的扩展卡尔曼滤波器相比，自适应容错扩展卡尔曼滤波器具有更强的抗干扰能力。另外，自适应容错扩展卡尔曼滤波器可以保持姿态估计精度。$\pm 0.8°$当不存在全区域红外干扰或大多数IRFPA数据可靠时。除导弹导航外，自适应容错扩展卡尔曼滤波器的框架可应用于几乎所有使用扩展卡尔曼滤波器的应用，例如飞机，车辆导航，室内定位和目标跟踪等。