When the target to be measured temperature is far away, and the prior information of the target such as the emissivity of the detected object can not be known, the traditional infrared single-band temperature measurement method will produce larger temperature measurement error. According to the characteristics of target infrared radiation spectrum, assuming that the target is grey body, this paper uses infrared dual-band temperature measurement algorithm and Monte Carlo method to extract the temperature feature of the object under test. The effectiveness of the algorithm is analyzed. The influence of parameters such as iteration times of the algorithm and the minimum error threshold of dual-band radiation ratio on the accuracy of target temperature inversion is simulated and analyzed. On this basis, the influence of different target emissivity, distance between wavebands and detection distance on target temperature inversion accuracy is analyzed. The results show that the two-band temperature measurement algorithm can extract the target temperature information quickly and accurately under the set parameters, and the temperature inversion error is related to the distance between infrared bands. This provides guidance for improving the accuracy of target temperature measurement in practical measurement.