Abstract:The instrument landing system has used various filters to improve accuracy in measurement, such as digital filters. But the system may still experience certain deviations between the measured values and the true values due to factors such as flight attitude, environment and measurement uncertainty, or some burrs and jumps in the measured values. Considering that filtering algorithms require a certain amount of computational data and hardware resources, the more complex the algorithm, the more resources it occupies. Starting from practical engineering applications, the Kalman filtering algorithm with high computational efficiency, strong stability, and low storage requirements is selected, which is applied in instrument landing airborne equipment to improve measurement accuracy.