Based on the characteristics of the noise source of airborne infrared search track (IRST) system, the detection probability model is established, and the effect of the threshold noise ratio (TNR) on the detection probability and the false alarm probability is analyzed in the detection process. The influences of the detection distance, target speed and combat environment on the detection probability are also analyzed based on the combat background. The dynamically setting of TNR in the process of detection is proposed and the specific solving method is presented. The value ranges of TNR are simulated under different mission requirements. With the solved TNR, the TNR-variable detection probability envelope is obtained. The research results show that compared with that by the method with a constant TNR, the detection probability envelope obtained by the TNR-variable method can adapt to the real-time change of air conditions, has a greater universality and a larger detection range.